Association of preschool children behavior and emotional problems with the parenting behavior of both parents

BACKGROUND Parental behaviors are key in shaping children’s psychological and behavioral development,crucial for early identification and prevention of mental health issues,reducing psychological trauma in childhood.AIM To investigate the relationship between parenting behaviors and behavioral and emotional issues in preschool children.METHODS From October 2017 to May 2018,7 kindergartens in Ma’anshan City were selected to conduct a parent self-filled questionnaire-Health Development Survey of Preschool Children.Children’s Strength and Difficulties Questionnaire(Parent Version)was applied to measures the children’s behavioral and emotional performance.Parenting behavior was evaluated using the Parental Behavior Inventory.Binomial logistic regression model was used to analyze the association between the detection rate of preschool children’s behavior and emotional problems and their parenting behaviors.RESULTS High level of parental support/participation was negatively correlated with conduct problems,abnormal hyperactivity,abnormal total difficulty scores and abnormal prosocial behavior problems.High level of maternal support/participation was negatively correlated with abnormal emotional symptoms and abnormal peer interaction in children.High level of parental hostility/coercion was positively correlated with abnormal emotional symptoms,abnormal conduct problems,abnormal hyperactivity,abnormal peer interaction,and abnormal total difficulty scores in children(all P<0.05).Moreover,paternal parenting behaviors had similarly effects on behavior and emotional problems of preschool children compared with maternal parenting behaviors(all P>0.05),after calculating ratio of odds ratio values.CONCLUSION Our study found that parenting behaviors are associated with behavioral and emotional issues in preschool children.Overall,the more supportive or involved the parents are,the fewer behavioral and emotional problems the children experience;conversely,the more hostile or controlling the parents are,the more behavioral and emotional problems the children face.Moreover,the impact of fathers’parenting behaviors on preschool children’s behavior and emotions is no less significant than that of mothers’parenting behaviors.

Comparative study on emotional behavior and parental job stress of only-child and non-only-child preschool children

BACKGROUND Studies have revealed that Children's psychological,behavioral,and emotional problems are easily influenced by the family environment.In recent years,the family structure in China has undergone significant changes,with more families having two or three children.AIM To explore the relationship between emotional behavior and parental job stress in only preschool and non-only preschool children.METHODS Children aged 3-6 in kindergartens in four main urban areas of Shijiazhuang were selected by stratified sampling for a questionnaire and divided into only and nononly child groups.Their emotional behaviors and parental pressure were compared.Only and non-only children were paired in a 1:1 ratio by class and age(difference less than or equal to 6 months),and the matched data were compared.The relationship between children's emotional behavior and parents'job stress before and after matching was analyzed.RESULTS Before matching,the mother's occupation,children's personality characteristics,and children's rearing patterns differed between the groups(P<0.05).After matching 550 pairs,differences in the children's parenting styles remained.There were significant differences in children's gender and parents'attitudes toward children between the two groups.The Strengths and Difficulties Questionnaire(SDQ)scores of children in the only child group and the Parenting Stress Index-Short Form(PSI-SF)scores of parents were significantly lower than those in the non-only child group(P<0.05).Pearson’s correlation analysis showed that after matching,there was a positive correlation between children's parenting style and parents'attitudes toward their children(r=0.096,P<0.01),and the PSI-SF score was positively correlated with children's gender,parents'attitudes toward their children,and SDQ scores(r=0.077,0.193,0.172,0.222).CONCLUSION Preschool children's emotional behavior and parental pressure were significantly higher in multi-child families.Parental pressure in differently structured families was associated with many factors,and preschool children's emotional behavior was positively correlated with parental pressure.

Relationship between Authoritative Parenting Style and Preschool Children’s Emotion Regulation:A Moderated Mediation Model

An authoritative parenting style has been shown to promote children’s emotion regulation in European-American family studies.However,little is known about how sleep problems and the child’s sibling status in Chinese families affect this relationship.Based on family system theory,this study attempts to better understand the relationship between authoritative parenting style and emotion regulation.Mothers of preschool children in Chinese kindergartens completed questionnaires about their children’s sleep habits,their authoritative parenting styles,and children’s emotion regulation.A total of 531 children participated in this study.Results showed that authoritative parenting was positively associated with emotional regulation.Sleep problems mediated the effects of authoritative parenting style on emotion regulation.The child’s sibling status moderated the mediating effects of sleep problems in authoritative parenting and emotion regulation relationships.Specifically,the relationship between the authoritative parenting style and sleep problems was significant for only children,while birth order had no significant influence on the authoritative parenting style and sleep problems in two-child families.These findings suggest that a lowauthoritative parenting style predicts low emotion regulation through sleep problems,and this depends on the child’s sibling status,indicating that children without siblings may impair emotion regulation due to increased sleep problems.

Impress of intergenerational emotional support on the depression in non-cohabiting parents

BACKGROUND Mental health is one of the important dimensions of health,while depression is an important indicator of mental health evaluation.AIM To investigate the association between intergenerational emotional support and depression of non-cohabiting parents(≥45 years old)in China.METHODS We used the fourth wave data from the China Health and Retirement Longitudinal Study(2015).The data was made up of ten main modules,the associated two datasets,and five constructed datasets.The first step is to select the corresponding module data according to the purpose of this study.Moreover,the data of the six modules are integrated by the unique ID code and we choose depression and non-cohabiting items as the selection conditions.4810 samples were selected,which mainly included data on intergenerational emotional support and the individual scores on depressive symptoms.RESULTS The average age of 4810 respondents was(60.56±14.613)years old.Females were accounted for more than half of the samples(52.6%).74.0%respondents from rural areas and approximately 63.3%of the participants had a chronic disease.The mean value of the CESD-10 score was 13.06(SD5.225).Both faces to face and phone contacts were protective factors on depression symptoms in the mid-aged and seniors in China(P<0.05).In terms of the frequency of face to face contact,the more frequently you met your parents,the lower your parents'depressive score was.Also,phone contact variable results are displayed as a positive correlation completely between inter-generational contacts from children and depressive symptoms in non-cohabiting parents in China.Children’s education level and income level were also reducing the risk of depression in noncohabiting parents.However,gender,children’s numerous,chronic disease and chronic disease number were the risk factors.CONCLUSION Intergenerational emotional support is associated with depressive symptoms in non-cohabiting parents in China.However,the relationship was also affected by other variables.

Relationship between negative emotions and perceived support among parents of hospitalized,critically ill children

Objectives:The purpose of this study was to describe relationships between negative emotions and perceived emotional support in parents of children admitted to the pediatric intensive care unit(PICU).Methods:This cross-sectional descriptive study conducted face-to-face interviews between January 2019 and January 2020.Study variables included depression(PHQ-9 Scale),anxiety(Emotional Distress-Anxiety-Short Form 8a),anger(Emotional Distress-Anger-Short Form 5a),fear(Fear-Affect Computerized Adaptive Test),somatic fear(Fear-Somatic Arousal-Fixed Form),loneliness(Revised 20-item UCLA Loneliness Scale),and perceived emotional support(Emotional Support-Fixed Form).Results:Eighty parents reported symptoms of depression 8.00(4.00,13.75),anxiety(23.43±7.80),anger(13.40±5.46),fear(72.81±27.26),somatic fear 9.00(6.00,12.75),loneliness(39.35±12.00),and low perceived emotional support(32.14±8.06).Parents who were young,single,low-income,and with limited-post secondary education reported greater loneliness and lower perceived emotional support.Fear correlated with depression(r=0.737,P<0.01)and anxiety(r=0.900,P<0.01).Inverse relationships were discovered between perceived emotional support and loneliness(r=-0.767,P<0.01),anger(r=-0.401,P<0.01),and depression(r=-0.334,P<0.01).Conclusions:The cluster of negative emotions identified will serve as potential targets for future interventions designed to enhance support for parents of critically ill children.

Stages of Emotional Experience of Parents of Children with Cochlear Implantation (CI)

Rehabilitation is a set of measures aimed at compensating or fully restoring the functions of the patient impaired by the disease. In the rehabilitation of children with a cochlear implant, a comprehensive, systematic approach is essential in the work of doctors, teachers, sign language teachers, psychologists, and families. Rehabilitation and social adaptation of children with a cochlear implant depend not only on specialists but also on the ability of parents to help the child organize educational activities in an optimistic mood and the ability to provide emotional support. This means that the role of parents in the way to successful rehabilitation is high, and therefore this topic is especially relevant today. .

Impact of propofol and sevoflurane anesthesia on cognition and emotion in gastric cancer patients undergoing radical resection

BACKGROUND Propofol and sevoflurane are commonly used anesthetic agents for maintenance anesthesia during radical resection of gastric cancer.However,there is a debate concerning their differential effects on cognitive function,anxiety,and depression in patients undergoing this procedure.AIM To compare the effects of propofol and sevoflurane anesthesia on postoperative cognitive function,anxiety,depression,and organ function in patients undergoing radical resection of gastric cancer.METHODS A total of 80 patients were involved in this research.The subjects were divided into two groups:Propofol group and sevoflurane group.The evaluation scale for cognitive function was the Loewenstein occupational therapy cognitive assessment(LOTCA),and anxiety and depression were assessed with the aid of the self-rating anxiety scale(SAS)and self-rating depression scale(SDS).Hemodynamic indicators,oxidative stress levels,and pulmonary function were also measured.RESULTS The LOTCA score at 1 d after surgery was significantly lower in the propofol group than in the sevoflurane group.Additionally,the SAS and SDS scores of the sevoflurane group were significantly lower than those of the propofol group.The sevoflurane group showed greater stability in heart rate as well as the mean arterial pressure compared to the propofol group.Moreover,the sevoflurane group displayed better pulmonary function and less lung injury than the propofol group.CONCLUSION Both propofol and sevoflurane could be utilized as maintenance anesthesia during radical resection of gastric cancer.Propofol anesthesia has a minimal effect on patients'pulmonary function,consequently enhancing their postoperative recovery.Sevoflurane anesthesia causes less impairment on patients'cognitive function and mitigates negative emotions,leading to an improved postoperative mental state.Therefore,the selection of anesthetic agents should be based on the individual patient's specific circumstances.

Adolescent suicide risk factors and the integration of socialemotional skills in school-based prevention programs

Adolescents are considered one of the most vulnerable groups affected by suicide.Rapid changes in adolescents’physical and mental states,as well as in their lives,significantly and undeniably increase the risk of suicide.Psychological,social,family,individual,and environmental factors are important risk factors for suicidal behavior among teenagers and may contribute to suicide risk through various direct,indirect,or combined pathways.Social-emotional learning is considered a powerful intervention measure for addressing the crisis of adolescent suicide.When deliberately cultivated,fostered,and enhanced,selfawareness,self-management,social awareness,interpersonal skills,and responsible decision-making,as the five core competencies of social-emotional learning,can be used to effectively target various risk factors for adolescent suicide and provide necessary mental and interpersonal support.Among numerous suicide intervention methods,school-based interventions based on social-emotional competence have shown great potential in preventing and addressing suicide risk factors in adolescents.The characteristics of school-based interventions based on social-emotional competence,including their appropriateness,necessity,cost-effectiveness,comprehensiveness,and effectiveness,make these interventions an important means of addressing the crisis of adolescent suicide.To further determine the potential of school-based interventions based on social-emotional competence and better address the issue of adolescent suicide,additional financial support should be provided,the combination of socialemotional learning and other suicide prevention programs within schools should be fully leveraged,and cooperation between schools and families,society,and other environments should be maximized.These efforts should be considered future research directions.

High-risk factors for delirium in severely ill patients and the application of emotional nursing combined with pain nursing

BACKGROUND Delirium is a neuropsychiatric syndrome characterized by acute disturbances of consciousness with rapid onset,rapid progression,obvious fluctuations,and preventable,reversible,and other characteristics.Patients with delirium in the intensive care unit(ICU)are often missed or misdiagnosed and do not receive adequate attention.AIM To analyze the risk factors for delirium in ICU patients and explore the applica-tion of emotional nursing with pain nursing in the management of delirium.METHODS General data of 301 critically ill patients were retrospectively collected,including histories(cardiovascular and cerebrovascular diseases,hypertension,smoking,alcoholism,and diabetes),age,sex,diagnosis,whether surgery was performed,and patient origin(emergency/clinic).Additionally,the duration of sedation,Richmond Agitation Sedation Scale score,combined emotional and pain care,ven-tilator use duration,vasoactive drug use,drainage tube retention,ICU stay du-ration,C-reactive protein,procalcitonin,white blood cell count,body tempe-rature,Acute Physiology and Chronic Health Evaluation II(APACHE II)score,and Sequential Organ Failure Assessment score were recorded within 24 h after ICU admission.Patients were assessed for delirium according to confusion assessment method for the ICU,and univariate and multivariate logistic regre-ssion analyses were performed to identify the risk factors for delirium in the patients.RESULTS Univariate logistic regression analysis was performed on the 24 potential risk factors associated with delirium in ICU patients.The results showed that 16 risk factors were closely related to delirium,including combined emotional and pain care,history of diabetes,and patient origin.Multivariate logistic regression analysis revealed that no combined emotional and pain care,history of diabetes,emergency source,surgery,long stay in the ICU,smoking history,and high APACHE II score were independent risk factors for de-lirium in ICU patients.CONCLUSION Patients with diabetes and/or smoking history,postoperative patients,patients with a high APACHE II score,and those with emergency ICU admission need emotional and pain care,flexible visiting modes,and early intervention to reduce delirium incidence.

Faster Region Convolutional Neural Network(FRCNN)Based Facial Emotion Recognition

Facial emotion recognition(FER)has become a focal point of research due to its widespread applications,ranging from human-computer interaction to affective computing.While traditional FER techniques have relied on handcrafted features and classification models trained on image or video datasets,recent strides in artificial intelligence and deep learning(DL)have ushered in more sophisticated approaches.The research aims to develop a FER system using a Faster Region Convolutional Neural Network(FRCNN)and design a specialized FRCNN architecture tailored for facial emotion recognition,leveraging its ability to capture spatial hierarchies within localized regions of facial features.The proposed work enhances the accuracy and efficiency of facial emotion recognition.The proposed work comprises twomajor key components:Inception V3-based feature extraction and FRCNN-based emotion categorization.Extensive experimentation on Kaggle datasets validates the effectiveness of the proposed strategy,showcasing the FRCNN approach’s resilience and accuracy in identifying and categorizing facial expressions.The model’s overall performance metrics are compelling,with an accuracy of 98.4%,precision of 97.2%,and recall of 96.31%.This work introduces a perceptive deep learning-based FER method,contributing to the evolving landscape of emotion recognition technologies.The high accuracy and resilience demonstrated by the FRCNN approach underscore its potential for real-world applications.This research advances the field of FER and presents a compelling case for the practicality and efficacy of deep learning models in automating the understanding of facial emotions.

Emotion Measurement Using Biometric Signal

In recent years, research on the estimation of human emotions has been active, and its application is expected in various fields. Biological reactions, such as electroencephalography (EEG) and root mean square successive difference (RMSSD), are indicators that are less influenced by individual arbitrariness. The present study used EEG and RMSSD signals to assess the emotions aroused by emotion-stimulating images in order to investigate whether various emotions are associated with characteristic biometric signal fluctuations. The participants underwent EEG and RMSSD while viewing emotionally stimulating images and answering the questionnaires. The emotions aroused by emotionally stimulating images were assessed by measuring the EEG signals and RMSSD values to determine whether different emotions are associated with characteristic biometric signal variations. Real-time emotion analysis software was used to identify the evoked emotions by describing them in the Circumplex Model of Affect based on the EEG signals and RMSSD values. Emotions other than happiness did not follow the Circumplex Model of Affect in this study. However, ventral attentional activity may have increased the RMSSD value for disgust as the β/θ value increased in right-sided brain waves. Therefore, the right-sided brain wave results are necessary when measuring disgust. Happiness can be assessed easily using the Circumplex Model of Affect for positive scene analysis. Improving the current analysis methods may facilitate the investigation of face-to-face communication in the future using biometric signals.

Rational and Continuous Measurement of Emotional-Fingerprint, Emotional-Quotient and Categorical vs Proportional Recognition of Facial Emotions with M.A.R.I.E., Second Half

Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the interfaces of verbal and emotional communications. The progress of AI is significant on the verbal level but modest in terms of the recognition of facial emotions even if this functionality is one of the oldest in humans and is omnipresent in our daily lives. Dysfunction in the ability for facial emotional expressions is present in many brain pathologies encountered by psychiatrists, neurologists, psychotherapists, mental health professionals including social workers. It cannot be objectively verified and measured due to a lack of reliable tools that are valid and consistently sensitive. Indeed, the articles in the scientific literature dealing with Visual-Facial-Emotions-Recognition (ViFaEmRe), suffer from the absence of 1) consensual and rational tools for continuous quantified measurement, 2) operational concepts. We have invented a software that can use computer-morphing attempting to respond to these two obstacles. It is identified as the Method of Analysis and Research of the Integration of Emotions (M.A.R.I.E.). Our primary goal is to use M.A.R.I.E. to understand the physiology of ViFaEmRe in normal healthy subjects by standardizing the measurements. Then, it will allow us to focus on subjects manifesting abnormalities in this ability. Our second goal is to make our contribution to the progress of AI hoping to add the dimension of recognition of facial emotional expressions. Objective: To study: 1) categorical vs dimensional aspects of recognition of ViFaEmRe, 2) universality vs idiosyncrasy, 3) immediate vs ambivalent Emotional-Decision-Making, 4) the Emotional-Fingerprint of a face and 5) creation of population references data. Methods: M.A.R.I.E. enables the rational, quantified measurement of Emotional Visual Acuity (EVA) in an individual observer and a population aged 20 to 70 years. Meanwhile, it can measure the range and intensity of expressed emotions through three Face- Tests, quantify the performance of a sample of 204 observers with hypernormal measures of cognition, “thymia” (defined elsewhere), and low levels of anxiety, and perform analysis of the six primary emotions. Results: We have individualized the following continuous parameters: 1) “Emotional-Visual- Acuity”, 2) “Visual-Emotional-Feeling”, 3) “Emotional-Quotient”, 4) “Emotional-Decision-Making”, 5) “Emotional-Decision-Making Graph” or “Individual-Gun-Trigger”, 6) “Emotional-Fingerprint” or “Key-graph”, 7) “Emotional-Fingerprint-Graph”, 8) detecting “misunderstanding” and 9) detecting “error”. This allowed us a taxonomy with coding of the face-emotion pair. Each face has specific measurements and graphics. The EVA improves from ages of 20 to 55 years, then decreases. It does not depend on the sex of the observer, nor the face studied. In addition, 1% of people endowed with normal intelligence do not recognize emotions. The categorical dimension is a variable for everyone. The range and intensity of ViFaEmRe is idiosyncratic and not universally uniform. The recognition of emotions is purely categorical for a single individual. It is dimensional for a population sample. Conclusions: Firstly, M.A.R.I.E. has made possible to bring out new concepts and new continuous measurements variables. The comparison between healthy and abnormal individuals makes it possible to take into consideration the significance of this line of study. From now on, these new functional parameters will allow us to identify and name “emotional” disorders or illnesses which can give additional dimension to behavioral disorders in all pathologies that affect the brain. Secondly, the ViFaEmRe is idiosyncratic, categorical, and a function of the identity of the observer and of the observed face. These findings stack up against Artificial Intelligence, which cannot have a globalist or regionalist algorithm that can be programmed into a robot, nor can AI compete with human abilities and judgment in this domain. *Here “Emotional disorders” refers to disorders of emotional expressions and recognition.

Rational and Continuous Measurement of the Emotional Decision Making in Visual Recognition of Facial Emotional Expressions with M.A.R.I.E.: First Half

Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the interfaces of verbal and emotional communications. The progress of AI is significant on the verbal level but modest in terms of the recognition of facial emotions even if this functionality is one of the oldest in humans and is omnipresent in our daily lives. Dysfunction in the ability for facial emotional expressions is present in many brain pathologies encountered by psychiatrists, neurologists, psychotherapists, mental health professionals including social workers. It cannot be objectively verified and measured due to a lack of reliable tools that are valid and consistently sensitive. Indeed, the articles in the scientific literature dealing with Visual-Facial-Emotions-Recognition (ViFaEmRe), suffer from the absence of 1) consensual and rational tools for continuous quantified measurement, 2) operational concepts. We have invented a software that can use computer-morphing attempting to respond to these two obstacles. It is identified as the Method of Analysis and Research of the Integration of Emotions (M.A.R.I.E.). Our primary goal is to use M.A.R.I.E. to understand the physiology of ViFaEmRe in normal healthy subjects by standardizing the measurements. Then, it will allow us to focus on subjects manifesting abnormalities in this ability. Our second goal is to make our contribution to the progress of AI hoping to add the dimension of recognition of facial emotional expressions. Objective: To study: 1) categorical vs dimensional aspects of recognition of ViFaEmRe, 2) universality vs idiosyncrasy, 3) immediate vs ambivalent Emotional-Decision-Making, 4) the Emotional-Fingerprint of a face and 5) creation of population references data. Methods: With M.A.R.I.E. enable a rational quantified measurement of Emotional-Visual-Acuity (EVA) of 1) a) an individual observer, b) in a population aged 20 to 70 years old, 2) measure the range and intensity of expressed emotions by 3 Face-Tests, 3) quantify the performance of a sample of 204 observers with hyper normal measures of cognition, “thymia,” (ibid. defined elsewhere) and low levels of anxiety 4) analysis of the 6 primary emotions. Results: We have individualized the following continuous parameters: 1) “Emotional-Visual-Acuity”, 2) “Visual-Emotional-Feeling”, 3) “Emotional-Quotient”, 4) “Emotional-Deci-sion-Making”, 5) “Emotional-Decision-Making Graph” or “Individual-Gun-Trigger”6) “Emotional-Fingerprint” or “Key-graph”, 7) “Emotional-Finger-print-Graph”, 8) detecting “misunderstanding” and 9) detecting “error”. This allowed us a taxonomy with coding of the face-emotion pair. Each face has specific measurements and graphics. The EVA improves from ages of 20 to 55 years, then decreases. It does not depend on the sex of the observer, nor the face studied. In addition, 1% of people endowed with normal intelligence do not recognize emotions. The categorical dimension is a variable for everyone. The range and intensity of ViFaEmRe is idiosyncratic and not universally uniform. The recognition of emotions is purely categorical for a single individual. It is dimensional for a population sample. Conclusions: Firstly, M.A.R.I.E. has made possible to bring out new concepts and new continuous measurements variables. The comparison between healthy and abnormal individuals makes it possible to take into consideration the significance of this line of study. From now on, these new functional parameters will allow us to identify and name “emotional” disorders or illnesses which can give additional dimension to behavioral disorders in all pathologies that affect the brain. Secondly, the ViFaEmRe is idiosyncratic, categorical, and a function of the identity of the observer and of the observed face. These findings stack up against Artificial Intelligence, which cannot have a globalist or regionalist algorithm that can be programmed into a robot, nor can AI compete with human abilities and judgment in this domain. *Here “Emotional disorders” refers to disorders of emotional expressions and recognition.

The Development of a Feeding Coparenting Scale for Japanese Parents of Fifth- and Sixth-Grade Elementary School Children

Aim: Recently, the role of feeding coparenting has gained attention in the child eating research field. The Feeding Coparenting Scale (FCS), a measure of how caregivers interact with their partners when feeding their children was developed in the United States in 2019. However, there is no valid and reliable measure to assess feeding coparenting among caregivers of school-aged children in Japan. Therefore, this study aimed to develop a Japanese version of the FCS (FCS-J) questionnaire for caregivers with school-aged children. Methods: This was a web-based cross-sectional survey completed by caregivers of children aged 10-12 years. A preliminary survey using interviews and a web-based survey was conducted and found that the translated items of the FCS into Japanese were understandable to Japanese people. The developed survey was administered to parents of children at an elementary school. The reliability of the survey was assessed using both test-retest reliability and internal consistency analysis. Exploratory factor analysis was used to test construct validity, and known population validity was examined in relation to attributes, marital satisfaction, and feeding tasks. Results: Findings with 135 parents of school-aged children showed good internal reliability and validity of the FCS-J. The mean score for the overall FCS-J score was 46.2 (SD = 6.2), with Cronbach’s α of 0.72. For the subscales, Cronbach’s α ranged from 0.75 to 0.79. In sum, the present study’s results support the three-factor structure of the FCS in Japanese caregivers in Japan. Conclusions: The developed FCS-J was found to have a certain degree of reliability and validity. In this study, a Japanese version of the FCS-J was developed. .

Expérience des parents faceàl’accompagnement pédiatrique en HAD:étude exploratoire qualitative Parents’Experience of Pediatric Home Care:A Qualitative Exploratory Study

Aim:To investigate parents’experience of home care for children in oncology in order to identify the benefits,expectations,and possible difficulties associated.Material and methods:A qualitative method was adopted,with non-directive interviews conducted with nine participants,then analyzed using thematic content analysis.Results:The main recurring themes in the discourse include:(1)relief,(2)positive representation of home,(3)positive representation of home care,and(4)negative representation of home care.For these parents,home care appears to be positive overall,even though the introduction of home care is often reported as a source of stress for them.Conclusion:These results must be interpreted with caution,but they do support previous research and highlight certain recommendations for further improving this experience,particularly for parents,but also for the sick child and the family.

Emotion Detection Using ECG Signals and a Lightweight CNN Model

Emotion recognition is a growing field that has numerous applications in smart healthcare systems and Human-Computer Interaction(HCI).However,physical methods of emotion recognition such as facial expressions,voice,and text data,do not always indicate true emotions,as users can falsify them.Among the physiological methods of emotion detection,Electrocardiogram(ECG)is a reliable and efficient way of detecting emotions.ECG-enabled smart bands have proven effective in collecting emotional data in uncontrolled environments.Researchers use deep machine learning techniques for emotion recognition using ECG signals,but there is a need to develop efficient models by tuning the hyperparameters.Furthermore,most researchers focus on detecting emotions in individual settings,but there is a need to extend this research to group settings aswell since most of the emotions are experienced in groups.In this study,we have developed a novel lightweight one dimensional(1D)Convolutional Neural Network(CNN)model by reducing the number of convolution,max pooling,and classification layers.This optimization has led to more efficient emotion classification using ECG.We tested the proposed model’s performance using ECG data from the AMIGOS(A Dataset for Affect,Personality and Mood Research on Individuals andGroups)dataset for both individual and group settings.The results showed that themodel achieved an accuracy of 82.21%and 85.62%for valence and arousal classification,respectively,in individual settings.In group settings,the accuracy was even higher,at 99.56%and 99.68%for valence and arousal classification,respectively.By reducing the number of layers,the lightweight CNNmodel can process data more quickly and with less complexity in the hardware,making it suitable for the implementation on the mobile phone devices to detect emotions with improved accuracy and speed.

Narrative nursing for negative emotions in patients with acute pancreatitis:Based on model construction and application

BACKGROUND Acute pancreatitis(AP),as a common acute abdomen disease,has a high incidence rate worldwide and is often accompanied by severe complications.Negative emotions lead to increased secretion of stress hormones,elevated blood sugar levels,and enhanced insulin resistance,which in turn increases the risk of AP and significantly affects the patient's quality of life.Therefore,exploring the intervention effects of narrative nursing programs on the negative emotions of patients with AP is not only helpful in alleviating psychological stress and improving quality of life but also has significant implications for improving disease outcomes and prognosis.AIM To construct a narrative nursing model for negative emotions in patients with AP and verify its efficacy in application.METHODS Through Delphi expert consultation,a narrative nursing model for negative emotions in patients with AP was constructed.A non-randomized quasi-experimental study design was used in this study.A total of 92 patients with AP with negative emotions admitted to a tertiary hospital in Nantong City of Jiangsu Province,China from September 2022 to August 2023 were recruited by convenience sampling,among whom 46 patients admitted from September 2022 to February 2023 were included in the observation group,and 46 patients from March to August 2023 were selected as control group.The observation group received narrative nursing plan,while the control group was given with routine nursing.Self-rating anxiety scale(SAS),self-rating depression scale(SDS),positive and negative affect scale(PANAS),caring behavior scale,patient satisfaction scale and 36-item short form health survey questionnaire(SF-36)were used to evaluate their emotions,satisfaction and caring behaviors in the two groups on the day of discharge,1-and 3-month following discharge.RESULTS According to the inclusion and exclusion criteria,a total of 45 cases in the intervention group and 44 cases in the control group eventually recruited and completed in the study.On the day of discharge,the intervention group showed significantly lower scores of SAS,SDS and negative emotion(28.57±4.52 vs 17.4±4.44,P<0.001),whereas evidently higher outcomes in the positive emotion score,Caring behavior scale score and satisfaction score compared to the control group(P<0.05).Repeated measurement analysis of variance showed that significant between-group differences were found in time effect,inter-group effect and interaction effect of SAS and PANAS scores as well as in time effect and inter-group effect of SF-36 scores(P<0.05);the SF-36 scores of two groups at 3 months after discharge were higher than those at 1 month after discharge(P<0.05).CONCLUSION The application of narrative nursing protocols has demonstrated significant effectiveness in alleviating anxiety,ameliorating negative emotions,and enhancing satisfaction among patients with AP.

The Emotional Intelligence and the Associated Factors among Nursing Students

Introduction: Emotional intelligence, or the capacity to cope one’s emotions, makes it simpler to form good connections with others and do caring duties. Nursing students can enroll a health team in a helpful and beneficial way with the use of emotional intelligence. Nurses who can identify, control, and interpret both their own emotions and those of their patients provide better patient care. The purpose of this study was to assess the emotional intelligence and to investigate the relationship and differences between emotional intelligence and demographic characteristics of nursing students. Methods: A cross-sectional study was carried out on 381 nursing students. Data collection was completed by “Schutte Self Report Emotional Intelligence Test”. Data were analyzed with the Statistical Package for Social Science. An independent t test, ANOVA, and Pearson correlation, multiple linear regression were used. Results: The results revealed that the emotional intelligence mean was 143.1 ± 21.6 (ranging from 33 to 165), which is high. Also, the analysis revealed that most of the participants 348 (91.3%) had higher emotional intelligence level. This finding suggests that nursing students are emotionally intelligent and may be able to notice, analyze, control, manage, and harness emotion in an adaptive manner. Also, academic year of nursing students was a predictor of emotional intelligence. Furthermore, there was positive relationship between the age and emotional intelligence (p < 0.05). The students’ ability to use their EI increased as they rose through the nursing grades. Conclusion: This study confirmed that the emotional intelligence score of the nursing students was high. Also, academic year of nursing students was a predictor of emotional intelligence. In addition, a positive relationship was confirmed between the emotional intelligence and age of nursing students. .

Multi-Objective Equilibrium Optimizer for Feature Selection in High-Dimensional English Speech Emotion Recognition

Speech emotion recognition(SER)uses acoustic analysis to find features for emotion recognition and examines variations in voice that are caused by emotions.The number of features acquired with acoustic analysis is extremely high,so we introduce a hybrid filter-wrapper feature selection algorithm based on an improved equilibrium optimizer for constructing an emotion recognition system.The proposed algorithm implements multi-objective emotion recognition with the minimum number of selected features and maximum accuracy.First,we use the information gain and Fisher Score to sort the features extracted from signals.Then,we employ a multi-objective ranking method to evaluate these features and assign different importance to them.Features with high rankings have a large probability of being selected.Finally,we propose a repair strategy to address the problem of duplicate solutions in multi-objective feature selection,which can improve the diversity of solutions and avoid falling into local traps.Using random forest and K-nearest neighbor classifiers,four English speech emotion datasets are employed to test the proposed algorithm(MBEO)as well as other multi-objective emotion identification techniques.The results illustrate that it performs well in inverted generational distance,hypervolume,Pareto solutions,and execution time,and MBEO is appropriate for high-dimensional English SER.

E2E-MFERC:AMulti-Face Expression Recognition Model for Group Emotion Assessment

In smart classrooms, conducting multi-face expression recognition based on existing hardware devices to assessstudents’ group emotions can provide educators with more comprehensive and intuitive classroom effect analysis,thereby continuouslypromotingthe improvementof teaching quality.However,most existingmulti-face expressionrecognition methods adopt a multi-stage approach, with an overall complex process, poor real-time performance,and insufficient generalization ability. In addition, the existing facial expression datasets are mostly single faceimages, which are of low quality and lack specificity, also restricting the development of this research. This paperaims to propose an end-to-end high-performance multi-face expression recognition algorithm model suitable forsmart classrooms, construct a high-quality multi-face expression dataset to support algorithm research, and applythe model to group emotion assessment to expand its application value. To this end, we propose an end-to-endmulti-face expression recognition algorithm model for smart classrooms (E2E-MFERC). In order to provide highqualityand highly targeted data support for model research, we constructed a multi-face expression dataset inreal classrooms (MFED), containing 2,385 images and a total of 18,712 expression labels, collected from smartclassrooms. In constructing E2E-MFERC, by introducing Re-parameterization visual geometry group (RepVGG)block and symmetric positive definite convolution (SPD-Conv) modules to enhance representational capability;combined with the cross stage partial network fusion module optimized by attention mechanism (C2f_Attention),it strengthens the ability to extract key information;adopts asymptotic feature pyramid network (AFPN) featurefusion tailored to classroomscenes and optimizes the head prediction output size;achieves high-performance endto-end multi-face expression detection. Finally, we apply the model to smart classroom group emotion assessmentand provide design references for classroom effect analysis evaluation metrics. Experiments based on MFED showthat the mAP and F1-score of E2E-MFERC on classroom evaluation data reach 83.6% and 0.77, respectively,improving the mAP of same-scale You Only Look Once version 5 (YOLOv5) and You Only Look Once version8 (YOLOv8) by 6.8% and 2.5%, respectively, and the F1-score by 0.06 and 0.04, respectively. E2E-MFERC modelhas obvious advantages in both detection speed and accuracy, which can meet the practical needs of real-timemulti-face expression analysis in classrooms, and serve the application of teaching effect assessment very well.