Sad Mood Research Articles

The relationship between irritability, depression and anxiety among Chinese college students during the COVID-19 pandemic: A network analysis

IntroductionIrritability, a common symptom included in the 5th Edition of Diagnostic and Statistical Manual of Mental Disorders (DSM-5), is thought to be associated with multiple emotional disorders. It is commonly seen among college students in isolation during the COVID-19 pandemic. However, its relation with anxiety and depression remains unclear. We aim to study the relation of irritability, anxiety and depression in Chinese college students during the COVID-19 pandemic by using network analysis to understand the co-occurrence of these three disorders.MethodsDuring the COVID-19 pandemic, we recruited 1516 college students from five general universities in China to complete the Irritability, Depression and Anxiety Scale (IDA-S) to analyze the symptom network of irritability, depression and anxiety. Specifically, we assessed the indices of strength centrality and bridge strength for each node in the network.ResultsSome strongest linkages were found among anxiety symptoms “nervous” and “panic” (weight = 0.36), depression symptoms “sad mood” and “amused” (weight = 0.32), inward irritability items “self-hurt” and “self-harm” (weight = 0.32) and outward items “rough” and “aggressive” (weight = 0.28). The anxiety symptom “panic” had the highest strength value, followed by the inward irritability symptom “annoyed”. The nodes “ease” and “sleep” had the lowest strength value. In addition, the anxiety symptom “relax” had the highest bridge strength value, followed by inward irritability symptom “annoyed”.ConclusionThis study explored the characteristics of a network of irritability, depression and anxiety symptoms among Chinese college students during the COVID-19 pandemic. We found that anxiety and irritability symptoms played an important role in the network. The findings provide evidence for prevention and intervention for college students' mental health problems during the COVID-19 pandemic.

Depression detection in social media comments data using machine learning algorithms

Depression is the next level of negative emotions. When a person is in a sad mood or going through a difficult situation and it is not leaving him and giving him pain continuously and he is unable to bear it anymore, that situation is called depression. The last stage of depression occurs in suicide. According to the World Health Organization (WHO), Currently, 4.4% of people in the world are currently suffering from depression. In 2021, fourteen thousand people committed suicide all over the world and the rating of suicide is increasing day by day. So, our study is to find depressed people by their comments, posts, or texts on social media. We collected almost 10,000 data from Facebook posts, comments, and YouTube comments. Data mining and machine learning (ML) algorithms make our work easier and play a big role in easily detecting a person’s emotions. We applied six classifiers to predict depression non-depression and found the best accuracy on a support vector machine (SVM).

Network analysis of comorbid insomnia and depressive symptoms among psychiatric practitioners during the COVID-19 pandemic.

Insomnia and depression are common mental health problems reported by mental health professionals during the COVID-19 pandemic. Network analysis is a fine-grained approach used to examine associations between psychiatric syndromes at a symptom level. This study was designed to elucidate central symptoms and bridge symptoms of a depression-insomnia network among psychiatric practitioners in China. The identification of particularly important symptoms via network analysis provides an empirical foundation for targeting specific symptoms when developing treatments for comorbid insomnia and depression within this population. A total of 10,516 psychiatric practitioners were included in this study. The Insomnia Severity Index (ISI) and 9-item Patient Health Questionnaire (PHQ-9) were used to estimate prevalence rates of insomnia and depressive symptoms, respectively. Analyses also generated a network model of insomnia and depression symptoms in the sample. Prevalence rates of insomnia (ISI total score ≥8), depression (PHQ-9 total score ≥5) and comorbid insomnia and depression were 22.2% (95% confidence interval: 21.4-22.9%), 28.5% (95% confidence interval: 27.6-29.4%), and 16.0% (95% confidence interval: 15.3-16.7%), respectively. Network analysis revealed that "Distress caused by sleep difficulties" (ISI7) and "Sleep maintenance" (ISI2) had the highest strength centrality, followed by "Motor dysfunction" (PHQ8) and "Sad mood" (PHQ2). Furthermore, the nodes "Sleep dissatisfaction" (ISI4), "Fatigue" (PHQ4), and "Motor dysfunction" (PHQ8) had the highest bridge strengths in linking depression and insomnia communities. Both central and bridge symptoms (ie, Distress caused by sleep difficulties, Sleep maintenance, Motor dysfunction, Sad mood, Sleep dissatisfaction, and Fatigue) should be prioritized when testing preventive measures and specific treatments to address comorbid insomnia and depression among psychiatric practitioners during the COVID-19 pandemic. Zhao N, Zhao Y-J, An F, etal. Network analysis of comorbid insomnia and depressive symptoms among psychiatric practitioners during the COVID-19 pandemic. J Clin Sleep Med. 2023;19(7):1271-1279.

Prevalence of depression and its association with quality of life in patients after pacemaker implantation during the COVID-19 pandemic: A network analysis.

This study was designed to investigate the prevalence and predictors of depression in patients after pacemaker implantation during the COVID-19 pandemic in addition to identifying specific depressive symptoms associated with quality of life (QOL) using network analysis (NA). This cross-sectional, observational study was conducted in China between July 1, 2021, and May 17, 2022. Descriptive analysis was used to calculate depression prevalence. Univariate analyses were used to compare differences in demographic and clinical characteristics between depressed and non-depressed patients following pacemaker implantation. Binary logistic regression analysis was used to assess factors independently associated with depression. Network analysis "expected influence," and flow function indexes were used to identify symptoms central to the depression network of the sample and depressive symptoms that were directly associated with QOL, respectively. Network stability was examined using a case-dropping bootstrap procedure. In total, 206 patients implanted with a pacemaker met the study entry criteria and completed the assessment. The overall prevalence of depression (PHQ-9 total score ≥ 5) was 39.92% [95% confidence interval (CI) = 29.37-42.47%]. A binary logistic regression analysis revealed that patients with depression were more likely to report a poor health status (p = 0.031), severe anxiety symptoms (p < 0.001), and fatigue (p < 0.001). In the network model for depression, "Sad mood," "Poor Energy," and "Guilt" were the most influential symptoms. "Fatigue" had the strongest negative association with QOL, followed by "Sad mood" and "Appetite". Depression is common among patients having undergone pacemaker implantation during the COVID-19 pandemic. Anxiety, central symptoms of depression (i.e., "Sad mood", "Poor Energy", and "Guilt") and depressive symptoms linked to QOL (i.e., "Sad mood", "Appetite", and "Fatigue") identified in this study are promising targets for interventions and preventive measures for depression in patients who have undergone pacemaker implants.

The effect of sad mood on early sensory event-related potentials to task-irrelevant faces

It has been shown that the perceiver’s mood affects the perception of emotional faces, but it is not known how mood affects preattentive brain responses to emotional facial expressions. To examine the question, we experimentally induced sad and neutral mood in healthy adults before presenting them with task-irrelevant pictures of faces while an electroencephalography was recorded. Sad, happy, and neutral faces were presented to the participants in an ignore oddball condition. Differential responses (emotional – neutral) for the P1, N170, and P2 amplitudes were extracted and compared between neutral and sad mood conditions. Emotional facial expressions modulated all the components, and an interaction effect of expression by mood was found for P1: an emotional modulation to happy faces, which was found in neutral mood condition, disappeared in sad mood condition. For N170 and P2, we found larger response amplitudes for both emotional faces, regardless of the mood. The results add to the previous behavioral findings showing that mood already affects low-level cortical feature encoding of task-irrelevant faces.

Psychiatric disorders in teleoperators : A series of 27 cases

IntroductionBy its nature, the activity of teleoperators seems to be a propitious environment for the development of psychosocial disorders, sometimes severeObjectivesTo study the frequency of psychiatric disorders among teleoperators and their impact on medical fitness for workMethodsThis is a retrospective descriptive epidemiological study. We examined the files of teleoperators who were referred to the occupational medicine department of Charles Nicolle between 2014 and 2022 for a medical opinion of aptitudeResultsA total of 82 cases were identified, 27 of which had psychological complaints. A clear female predominance was noted (21). The average age was 38.22+-6.536 years. All the patients were telephonists at the call-taking station with an average professional seniority of 9.3+-3.395 years. The symptoms noted were: sad mood (19), irritability (15), anxiety (10), sleep disorders (8), loss of vital impetus (8), neurovegetative signs (6), psychomotor slowing (5), concentration and memory disorders (3). Only one patient had suicidal thoughts. Symptoms had been evolving for an average of 34.32+-34.527 months. Psychiatric follow-up was noted in 16 patients. The diagnoses retained were: anxiety and depressive disorder (19), adjustment disorder (4), panic disorder (2), obsessive-compulsive disorder (1), and a satisfactory state of health (1). In some cases, the evolution was marked by complications: addiction(1), tonic stuttering with phobic disorder(1) and speech disorder(1). The prescribed treatments were: an antidepressant(2), an antidepressant-anxiety combination(8) and psychotropic drugs(2). Concerning the ability to work, 21 patients required an eviction from call taking (definitive (9) or temporary for 3 months (7) or 6 months (5) with re-evaluation of the medical ability to work at the end of this period), 1patient had an eviction from night work and an other had a reduction of the working hours.ConclusionsTeleoperators are exposed to several risks which can affect both their mental and physical health and put their medical fitness for work at risk.Disclosure of InterestNone Declared

2022 HES PRESIDENTIAL ADDRESS: THE HISTORY OF ECONOMICS AS ECONOMIC SELF-PORTRAITURE

I wrote this address during the first weeks of the murderous and devastating invasion of Russia in Ukraine, in a fluctuating mood of anger and sadness. My aim was addressing the issue of the use of history to legitimize ideology, and I was contemplating how I could convince you of the urgency of this issue, and then this war broke out.

Impact of response shift effects in the assessment of self-reported depression during treatment: Insights from a rTMS versus Venlafaxine randomized controlled trial

PurposePatient-Reported Outcomes are essential to properly assess treatment effectiveness in randomized clinical trial (RCT) for Major Depressive Disorder (MDD). MDD self-assessment may vary over time depending on change in the meaning of patients’ self-evaluation of depression, i.e. Response Shift (RS). Our aim was to investigate RS and its impact on different depression domains in a clinical trial comparing rTMS versus Venlafaxine. MethodsThe occurrence and type of RS was determined using Structural Equation Modeling applied to change over time in 3 domains (Sad Mood, Performance Impairment, Negative Self-Reference) of the short-form Beck Depression Inventory (BDI-13) in a secondary analysis of a RCT on 170 patients with MDD treated by rTMS, venlafaxine or both. ResultsRS was evidenced in the venlafaxine group in the Negative Self-Reference and Sad Mood domains. ConclusionRS effects differed between treatment arms in self-reported depression domains in patients with MDD. Ignoring RS would have led to a slight underestimation of depression improvement, depending on treatment group. Further investigations of RS and advancing new methods are needed to better inform decision making based on Patient-Reported Outcomes.

Effects of Mood on Psychophysiological Detection of Concealed Information and the Relation to Self-Assessed Lying Ability

The present study examined the effects of mood on physiological responses in the Concealed Information polygraph Test and the relation to self-assessed lying ability. One hundred and eight undergraduate students self-assessed their lie-telling ability, committed a mock theft, and were asked to conceal information related to the crime. Participants were then divided into three equal groups: two groups were asked to provide a detailed written account of either a happy or sad event in order to induce a happy or sad mood, while the third group served as a neutral group. Participants then underwent a polygraph test and were asked to try to avoid detection. An induced happy or sad mood tended to lower relative skin conductance responses to critical (crime related) items and enhance relative cardiovascular responses. Relative respiration responses to critical items obtained for the sad mood condition were more robust than the ones obtained for the happy mood condition. Under induced sad and happy moods, those who self-rated their lie-telling ability as high showed enhanced cardiovascular responsivity to critical items. These results were limited to the initial phase of the test. We discussed possible motivational explanations and implications for the Concealed Information polygraph test.

PREVALENCE OF PSYCHIATRIC DISORDERS IN VIOLENT CRIME BEHAVIOUR: CLERKED CLIENTS LIST, FEDERAL MEDICAL CENTRE, KEFFI

Prevalence of psychiatric disorders and violent crime is unprecedented in the national health emergency sectors especially FMC, Keffi health in a box. Psychiatric clients were recorded among the psychiatric cases in the clinic in federal medical centre, Keffi. The cardinal objective of the study is to investigate the prevalence of psychiatric disorders and ways to curtail incidences of psychosocial disorders in the mental behaviour process of the clients under examination. The current states of disturbance of psychiatric patient clinic were characterized by schizophrenia disorder, anxiety disorder, depression disorder, alcoholic, antisocial personality disorder and mental illness and violent crime behaviour. Clinical depression and bipolar disorder were characterized by profoundly sad mood, overwhelming feelings of self-blame, guilt, and worthlessness, appetite disturbance in a recurrent thought of death or suicide. The study revealed that the effective prevalence and treatment for psychiatric clients will enhance management of the psychosocial disorder and the recovering of health well- being of the psychiatric patient’s clinic. The study concluded and recommends that the psychiatric disorders and violent crime were assessed through medical examination and national registers with reported incident psychotic symptoms. The pattern of inner experience and behaviour of violent crime is a significant health problem causing severe medical and social problems, considerable human suffering a huge economic cost. The prevalence of crime rates may supply more information about criminal behaviour than crime registers because of the high rate of unregistered less severe violent crime and therefore underestimate the psychiatric disorders and criminal behaviour.

Cyberbully victimization and its association with residual depressive symptoms among clinically stable adolescents with psychiatric disorders during the COVID-19 pandemic: A perspective from network analysis.

This study examined the prevalence of cyberbullying and its relationship with residual depressive symptoms in this patient population during the COVID-19 outbreak using network analysis. This was a multicenter, cross-sectional study. Adolescent patients attending maintenance treatment at outpatient departments of three major psychiatric hospitals were included. Experience of cyberbullying was measured with a standard question, while the severity of Internet addiction and depressive symptoms were measured using the Internet Addiction Test and the Patient Health Questionnaire-9, respectively. The network structure of depression and cyberbully were characterized and indices of "Expected Influence" was used to identify symptoms central to the network. To identify particular symptoms that were directly associated with cyberbully, the flow function was used. Altogether 1,265 patients completed the assessments. The overall prevalence of cyberbullying was 92.3% (95% confidence interval (CI): 90.8-93.7%). Multiple logistic regression analysis revealed that male gender (p = 0.04, OR = 1.72, 95%CI: 1.04-2.85) was significantly associated with higher risk of cyberbullying, while a relapse of illness during the COVID-19 pandemic was significantly associated with a lower risk of cyberbullying (p = 0.03, OR = 0.50, 95%CI: 0.27-0.93). In the network of depression and cyberbully, "Sad mood," "Anhedonia" and "Energy" were the most central (influential) symptoms. Furthermore, "Suicidal ideation" had the strongest negative association with cyberbully followed by "Guilt". During the COVID-19 pandemic, the experience of cyberbullying was highly prevalent among clinically stable adolescent psychiatric patients, particularly male patients. This finding should raise awareness of this issue emphasizing the need for regular screening and interventions for adolescent patients. Central symptoms (e.g., "Sad mood," "Anhedonia" and "Energy") identified in this study should be targeted in interventions and preventive measures.

Factors Determining the Mood and Emotions of Nurses Working in Pediatric Wards-A Pilot Study.

Mood and emotions are important aspects of social interactions. In recent years, there has been a growing interest in the participation of these emotional states in the implementation of tasks resulting from specific professions. The aim of the study is to identify the factors that determine the mood and emotions of nurses working in pediatric wards. The pilot studies presented in the paper were carried out using the diagnostic survey method. The collected data were obtained from the authors' own questionnaire and the standardized measurement tool "Scale for Measuring Mood and Six Emotions" by Bogdan Wojciszke and Wiesław Baryła. The study included 121 nurses working in hospital pediatric wards. The survey questionnaire results were obtained online using Google Forms. Self-assessment of the health condition of nurses is statistically significantly correlated with all emotions and mood (p < 0.05). The better the self-assessment of health, the greater the positive mood measured by the General Mood Scale (GMS) and Mood Scales (MS). The financial situation showed a statistically significant correlation with guilt (p = 0.048), sadness (p = 0.041), and negative mood (p = 0.035). Single people, regardless of gender, were characterized by a greater experience of love (H = 13.497; p < 0.001). The higher the education, the greater the experience of love (p = 0.009). For people with specialization, the presence of negative emotions such as anger (p = 0.039) and guilt (p = 0.049) turned out to be statistically significant. The better the health of children staying in the ward, the higher the negative mood of nurses (p = 0.035). There was a statistically significant relationship between certain demographic factors, self-assessment of health conditions with the specificity of working in pediatric wards, and the experience of mood and different emotions by nurses working with pediatric inpatients.

Emotionally congruent music and text increase immersion and appraisal.

Numerous studies indicate that listening to music and reading are processes that interact in multiple ways. However, these interactions have rarely been explored with regard to the role of emotional mood. In this study, we first conducted two pilot experiments to assess the conveyed emotional mood of four classical music pieces and that of four narrative text excerpts. In the main experiment, participants were asked to read the texts while listening to the music and to rate their emotional state in terms of valence, arousal, and dominance. Subsequently, they rated text and music of the multisensory event in terms of the perceived mood, liking, immersion, and music-text fit. We found a mutual carry-over effect of happy and sad moods from music to text and vice versa. Against our expectations, this effect was not mediated by the valence, arousal, or dominance experienced by the subject. Moreover, we revealed a significant interaction between music mood and text mood. Texts were liked better, they were classified as of better quality, and participants felt more immersed in the text if text mood and music mood corresponded. The role of mood congruence when listening to music while reading should not be ignored and deserves further exploration.

Comparing the centrality symptoms of major depressive disorder samples across junior high school students, senior high school students, college students and elderly adults during city lockdown of COVID-19 pandemic—A network analysis

IntroductionRecently, in the view of network analysis, depression has been conceptualized as a complex and dynamic network model combining individual symptoms. To date, no studies have systematically examined and compared depressive symptom networks across different populations. MethodsA total of 36,105 participants were recruited and asked to complete the Patient Health Questionnaire-9 among junior high school students, senior high school students, college students, and elderly adults who were more susceptible to depression during the COVID-19 lockdown in China. In the analysis, we applied the optimal cutoff score ≥ 8 for students and a score ≥ 6 for elderly adults to identify 5830 participants who were likely to be depressed. The index of “strength” was used to identify central symptoms in the network structure. ResultsThe results showed that Sad Mood was the most central symptom among junior high school students, senior high school students, and college students, but the most central symptom in the elderly was Guilt. Among the top three central symptoms, Suicide Ideation was unique to senior high school students, while Anhedonia was most prevalent among college students. Guilt - Suicide Ideation, Anhedonia – Energy, Anhedonia - Sad Mood, and Sleep – Energy showed the strongest association among junior and senior high school students, college students, and elderly adults, respectively. NCT (i.e., Network Comparison Test) suggested that the network's global connectivity was ultimately inconsistent, but the network structure remained roughly intact. ConclusionIn treatment, targeting central symptoms may be critical to alleviating depression.

Inter-relationships of depressive and anxiety symptoms with suicidality among adolescents: A network perspective

BackgroundPersons with suicidality including suicidal ideation (SI), suicide plans (SP) and/or suicide attempts (SA) are at higher risk for future suicide than those without suicidality. To reduce the risk of future suicide, it is important to understand symptoms of emotional distress that have the strongest links with SI, SP and SA. This network analysis examined item-level relations of depressive and anxiety symptoms with suicidality among adolescents during the COVID-19 pandemic. MethodsAdolescents between 12 and 20 years of age were assessed with the Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder Scale (GAD-7), and individual binary reponse (no/yes) items assessing SI, SP, and SA during the pandemic. The structure of depressive symptoms, anxiety symptoms and suicidality was characterized using “Expected Influence” and “Bridge Expected Influence” as centrality indices in the symptom network. Network stability was tested using a case-dropping bootstrap procedure. Node-specific predictive betweenness was computed to examine short paths of anhedonia, other depressive symptoms and anxiety symptoms with suicidality. A Network Comparison Test (NCT) was conducted to examine whether network characteristics differed based on gender. ResultsPrevalence rates of depressive symptoms, anxiety symptoms, and suicidality were 44.60 % (95% confidence interval (CI) = 41.53–47.67 %), 31.12 % (95%CI = 28.26–33.98 %), and 16.95 % (95%CI = 14.63–19.26 %), respectively, in the study sample. The network analysis identified GAD3 (“Worry too much”) as the most central symptom, followed by GAD6 (“Irritability”) and PHQ6 (“Guilt”) in the sample. Additionally, PHQ6 (“Guilt”), GAD6 (“Irritability”), and PHQ2 (“Sad mood”) were bridge nodes linking depressive and anxiety symptoms with suicidality. A flow network indicated that the connection between S (“Suicidality”) and PHQ6 (“Guilt”) reflected the strongest connection, followed by connections of S (“Suicidality”) with GAD2 (“Uncontrollable worrying”), and S (“Suicidality”) with PHQ2 (“Sad mood”). Finally, PHQ2 (“Sad mood”) was the main bridge node linking anhedonia with other depressive and anxiety symptoms and suicidality in the sample. ConclusionsFindings highlight the potential importance of reducing specific depressive and anxiety symptoms as possible means of reducing suicidality among adolescents during the pandemic. Central symptoms and key bridge symptoms identified in this study should be targeted in suicide prevention for at-risk adolescents.

Suicide ideation and anhedonia among clinically stable adolescents with the recurrent depressive disorder during the COVID-19 pandemic: A network perspective

BackgroundAnhedonia is a suicide risk factor among adolescent patients with recurrent depressive disorder (depression hereafter). This study examined associations between suicidal ideation (SI) and residual depressive symptoms (RSD), including anhedonia, among clinically stable adolescents with depression. MethodA network analysis was performed to examine the association between RDS and SI among adolescents with depression. Node-specific predictive betweenness was computed to examine short paths between anhedonia and SI. Additionally, a Network Comparison Test (NCT) was conducted to examine gender differences in derived network model characteristics. ResultsThe network analysis identified close associations of PHQ9 (“Suicide ideation”) with PHQ1 (“Anhedonia”) as well as some other RDS including PHQ6 (“Guilt”), PHQ2 (“Sad mood”) and PHQ8 (“Motor disturbances”). Additionally, PHQ2 (“Sad mood”) and PHQ4 (“Fatigue”) were the main bridge nodes linking anhedonia and SI. Comparisons of network models did not find significant differences in network global strength or edge weights. LimitationCausal relations between anhedonia and SI could not be determined due to the cross-sectional study design. ConclusionsSI was directly related to Anhedonia in addition to Guilt, Sad mood and Motor disturbances. Sad mood and Fatigue were the main bridge nodes linking Anhedonia and SI. To reduce the risk of SI among clinically stable adolescents with depression during the COVID-19 pandemic, specific RDS including Anhedonia, Guilt, Sad mood, Motor disturbances and Fatigue should be targeted in interventions.

The Dynamic Interplay of Anxious and Depressive Symptoms in a Sample of Undergraduate Students

The network perspective on psychopathology suggests that mental disorders can be regarded as networks of elements that influence each other. In this study, we used network analysis to explore the temporal interactions of anxiety and depression symptoms at the level of day-to-day experiences and find potential explanatory pathways for their comorbidity. We collected intensive longitudinal data from a sample of undergraduate students and fitted a Multilevel Vector Autoregressive model on GAD and MDD DSM-5 symptoms. “Sad mood” and “Concentration difficulties” were responsible for the most connections between anxiety and depression symptoms and were also among the most central symptoms. It is possible that anxio-depressive comorbidity can be explained by the presence of “Sad mood” and “Concentration difficulties” and targeting these two symptoms in therapy can lead to beneficial effects in comorbid cases.

Network analysis of anxiety and depression in the functionally impaired elderly.

Evidence from previous studies has confirmed that functionally impaired elderly individuals are susceptible to comorbid anxiety and depression. Network theory holds that the comorbidity emerges from interactions between anxiety and depression symptoms. This study aimed to investigate the fine-grained relationships among anxiety and depression symptoms in the functionally impaired elderly and identify central and bridge symptoms to provide potential targets for intervention of these two comorbid disorders. A total of 325 functionally impaired elderly individuals from five communities in Xi'an, China, were recruited for our investigation. The GAD-7 and PHQ-9 were used to measure anxiety and depression, respectively. SPSS 22.0 software was used for descriptive statistics, and R 4.1.1 software was used for network model construction, expected influence (EI) evaluation and bridge expected influence (BEI) evaluation. In the network, there were 35 edges (indicating partial correlations between symptoms) across the communities of anxiety and depression, among which the strongest edge was A1 "Nervousness or anxiety"-D2 "Depressed or sad mood." A2 "Uncontrollable worry" and D2 "Depressed or sad mood" had the highest EI values in the network, while A6 "Irritable" and D7 "Concentration difficulties" had the highest BEI values of their respective community. In the flow network, the strongest direct edge of D9 "Thoughts of death" was with D6 "Feeling of worthlessness." Complex fine-grained relationships exist between anxiety and depression in functionally impaired elderly individuals. "Uncontrollable worry," "depressed or sad mood," "irritable" and "concentration difficulties" are identified as the potential targets for intervention of anxiety and depression. Our study emphasizes the necessity of suicide prevention for functionally impaired elderly individuals, and the symptom "feeling of worthlessness" can be used as an effective target.

Functional Profile of Older Adults Hospitalized in Rehabilitation Units of the National Network of Integrated Continuous Care of Portugal: A Longitudinal Study.

The success of healthy aging depends on the ability of countries to study and act on frailty in the elderly, control chronic diseases, improve functional capacity and prevent cognitive decline and social interaction. (1) to evaluate the functional profile of older adults hospitalized in a Unit of the National Network of Integrated Continuous Care of Portugal; and (2) to assess the relationship between functional profile and age, gender, level of education and emotional state. Longitudinal study with a population of 59,013 older adults (65 years or older) hospitalized in Medium-Term Care and Rehabilitation Units in Portugal. Older age (≥85 years), no school attendance, low body mass index and presence of sad or depressed mood were predictive factors for a deficit in functional capacity. We identified significant improvements in rehabilitation, but after 210 days of hospitalization, older people incurred a loss of functionality. Total compensation needs were typified by severe deficits in self-care and functional capacity: 47.1%. A moderate deficit was present in 43.1%, and a slight self-care and functional deficit occurred in 9.8% of the individuals. Knowing the determinants of functional capacity and self-care needs will make it possible to define priority intervention groups and implement quality and financing models based on gains in functionality.

A network analysis of anxiety and depression symptoms among Chinese nurses in the late stage of the COVID-19 pandemic.

Nurses are at high risk for depression and anxiety symptoms after the outbreak of the COVID-19 pandemic. We aimed to assess the network structure of anxiety and depression symptoms among Chinese nurses in the late stage of this pandemic. A total of 6,183 nurses were recruited across China from Oct 2020 to Apr 2021 through snowball sampling. We used Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder scale-7 (GAD-7) to assess depression and anxiety, respectively. We used the Ising model to estimate the network. The index "expected influence" and "bridge expected influence" were applied to determine the central symptoms and bridge symptoms of the anxiety-depression network. We tested the stability and accuracy of the network via the case-dropping procedure and non-parametric bootstrapping procedure. The network had excellent stability and accuracy. Central symptoms included "restlessness", "trouble relaxing", "sad mood", and "uncontrollable worry". "Restlessness", "nervous", and "suicidal thoughts" served as bridge symptoms. Restlessness emerged as the strongest central and bridge symptom in the anxiety-depression network of nurses. Intervention on depression and anxiety symptoms in nurses should prioritize this symptom.