scholarly journals Network Analysis of Depressive Symptoms Among Residents of Wuhan in the Later Stage of the COVID-19 Pandemic

2021 ◽  
Vol 12 ◽  
Author(s):  
Na Zhao ◽  
Wen Li ◽  
Shu-Fang Zhang ◽  
Bing Xiang Yang ◽  
Sha Sha ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Network Analysis ◽  
Network Structure ◽  
Sleep Problems ◽  
Cross Sectional Study ◽  
Snowball Sampling ◽  
Cross Sectional ◽  
Sad Mood ◽  
Global Strength ◽  
Motor Disturbances

Background: Depression has been a common mental health problem during the COVID-19 epidemic. From a network perspective, depression can be conceptualized as the result of mutual interactions among individual symptoms, an approach that may elucidate the structure and mechanisms underlying this disorder. This study aimed to examine the structure of depression among residents in Wuhan, the epicenter of the COVID-19 outbreak in China, in the later stage of the COVID-19 pandemic.Methods: A total of 2,515 participants were recruited from the community via snowball sampling. The Patient Health Questionnaire was used to assess self-reported depressive symptoms with the QuestionnaireStar program. The network structure and relevant centrality indices of depression were examined in this sample.Results: Network analysis revealed Fatigue, Sad mood, Guilt and Motor disturbances as the most central symptoms, while Suicide and Sleep problems had the lowest centrality. No significant differences were found between women and men regarding network structure (maximum difference = 0.11, p = 0.44) and global strength (global strength difference = 0.04; female vs. male: 3.78 vs. 3.83, p = 0.51), a finding that suggests there are no gender differences in the structure or centrality of depressive symptoms.Limitations: Due to the cross-sectional study design, causal relationships between these depressive symptoms or dynamic changes in networks over time could not be established.Conclusions: Fatigue, Sad mood, Guilt, and Motor disturbances should be prioritized as targets in interventions and prevention efforts to reduce depression among residents in Wuhan, in the later stage of the COVID-19 pandemic.

scholarly journals Applying Network Analysis to Understand Depression and Substance Use in Indian Adolescents

2019 ◽  
Author(s):  
Akash Wasil ◽  
Katherine E. Venturo-Conerly ◽  
Sachin Shinde ◽  
Vikram Patel ◽  
Payton J. Jones
Keyword(s):  
Substance Use ◽  
Depressive Symptoms ◽  
Network Analysis ◽  
Sleep Problems ◽  
A Priori ◽  
World Health ◽  
Future Research ◽  
Cross Sectional ◽  
Indian Adolescents ◽  
Sad Mood

AbstractIntroduction: Network analysis has been used to better understand relationships between depressive symptoms. Existing work has rarely examined networks of adolescents or individuals in non-western countries. Methods: We used data from 13,035 adolescents (52.5% male; Mage = 13.8) from Bihar, a low-resource state in India. Depression was measured using the Patient Health Questionnaire-9, and substance use was measured using a questionnaire adapted from the World Health Organization. We modeled a network of depressive symptoms and a network examining connections between depressive symptoms and substance use. Results: The most commonly reported depressive symptoms were sleep problems and poor appetite. In the depression network, feeling like a failure and sad mood were the most central symptoms, and somatic symptoms clustered together. To our surprise, depressive symptoms were only weakly associated with substance use. Limitations: Our study uses cross-sectional data, which are not sufficient to draw causal inferences about the relationships between symptoms. Additionally, we used an exploratory data-driven approach, and we did not pose a priori hypotheses about the relationships between symptoms. Discussion: Our findings suggest that feelings like a failure and sad mood are highly central symptoms in Indian adolescents; future research may examine if these symptoms are strong targets for intervention. Sad mood has commonly been identified as a central symptom of depression in western samples, while feeling like a failure has not. We offer avenues for future research, illustrating how network analysis may enhance our ability to understand, prevent, and treat psychopathology in LMICs.

The buffering role of positive affect on the association between pain intensity and pain related outcomes

2017 ◽  
Vol 14 (1) ◽  
pp. 91-97 ◽  
Author(s):  
Ivan S.K. Thong ◽  
Gabriel Tan ◽  
Mark P. Jensen
Keyword(s):  
Chronic Pain ◽  
Depressive Symptoms ◽  
Negative Affect ◽  
Positive Affect ◽  
Pain Intensity ◽  
Sleep Problems ◽  
Cross Sectional Study ◽  
Pain Interference ◽  
Cross Sectional ◽  
The Impact

AbstractObjectivesChronic pain is a significant problem worldwide and is associated with significant elevations in negative affect, depressive symptoms, sleep problems, and physical dysfunction. Positive affect could potentially buffer the impact of pain on patient functioning. If it does, then positive affect could be directly targeted in treatment to benefit individuals with chronic pain. The purpose of this study was to test for such moderating effects.MethodsThis was a cross-sectional study, we administered measures of pain intensity, depressive symptoms, sleep problems, pain interference, and positive and negative affect to 100 individuals with chronic back or knee pain in a single face-to-face assessment session.ResultsThe associations between pain intensity and negative affect, and between pain intensity and depressive symptoms were moderated by positive affect. This moderation effect was explained by the fact that participants with low positive affect evidenced strong associations between pain intensity and both depression and negative affect; participants with high positive affect, on the other hand, evidenced weak and non-significant associations between pain intensity and both depression and negative affect. Positive affect did not moderate the associations between pain intensity and either sleep problems or pain interference.ConclusionThe findings are consistent with the possibility that positive affect may buffer the impact of pain intensity on negative affect and depressive symptoms. Longitudinal and experimental research is needed to determine the potential benefits of treatments that increase positive affect on negative affect and depressive symptoms in chronic pain populations.ImplicationsThe study findings suggest the possibility that “positive psychology” interventions which increase positive affect could benefit individuals with chronic pain by reducing the impact of pain on negative outcomes. Research to test this possibility is warranted.

scholarly journals Feelings of Worthlessness Links Depressive Symptoms and Parental Stress: A Network Analysis During the COVID-19 Pandemic

2021 ◽  
Author(s):  
Nora Skjerdingstad ◽  
Miriam S. Johnson ◽  
Sverre Urnes Johnson ◽  
Asle Hoffart ◽  
Omid V. Ebrahimi
Keyword(s):  
Depressive Symptoms ◽  
Network Analysis ◽  
Parental Stress ◽  
Network Models ◽  
Cross Sectional Study ◽  
Depression Symptoms ◽  
Health State ◽  
Cross Sectional ◽  
Psychological States ◽  
Influential Node

The prevalent co-occurrence between parental stress and depression has been previously established prior to and during the COVID-19 pandemic outbreak. However, no studies to date have identified the connections through which these symptom domains interact with each other to emerge into a complex and detrimental mental health state, along with the plausible mechanistic variables that may play key roles in maintaining parental stress and depression. The aim of this research is to uncover these interactions in a period where parents experience heighted demands and stress as a consequence of the strict social distancing protocols. Network analysis is utilized to examine parental stress and depressive symptoms during the COVID-19 pandemic in a large cross-sectional study (N = 2868) of parents. Two graphical Gaussian graphical network models were estimated, one in which only parental stress and depression symptoms were included, and another in which several mechanistic variables were added. Expected influence and bridge expected influence revealed that feeling worthless was the most influential node in the symptoms network and bridged the two psychological states. Among the mechanistic variables, worry and rumination was specifically relevant in the depressive cluster of symptoms, and self-criticism was connected to both constructs. The study display that the co-occurrence of parental stress and depression have specific pathways, were manifested through feelings of worthlessness, and have specific patterns of connection to important mechanisms of psychopathology. The results are of utility when aiming to avoid the constellation of co-occurring parental stress and depressive symptoms during the pandemic.

scholarly journals Relationship between sleep characteristics and depressive symptoms in last trimester of pregnancy

1970 ◽  
Vol 19 (4) ◽  
pp. 2934-2944
Author(s):  
Gülçin Nacar
Keyword(s):  
Depressive Symptoms ◽  
Pregnant Women ◽  
Rating Scale ◽  
Sleep Problems ◽  
Relevant Literature ◽  
Cross Sectional Study ◽  
Sleep Habits ◽  
Cross Sectional ◽  
Face To Face

Background: Sleep problems during pregnancy may cause many complications that reduce quality of life.Aim: This study aims to determine the relationship between pregnant women's sleep characteristics and depressive symptoms.Methods: A hospital-based, cross-sectional study was conducted. Pregnant women were selected from the population by using the an improbable random sampling method. This study sample included 436 pregnant women who met the study’s inclusion criteria. To collect data, this study used an information form that was developed by the researcher after reviewing relevant literature, the Women's Health Initiative Insomnia Rating Scale (WHIIRS), and the Beck Depression Inventory (BDI). The researchers used face-to-face interviews method to collect data from the participants, pregnant women who were examined in the polyclinic.Results: This study found that 36% of participating pregnant women reported insomnia, and 38.1% experienced depressive symptoms. It also determined that participants who had problems with insomnia, who experienced a change in sleep habits, and who did not wake up feeling rested experienced depressive symptoms 1.64, 2.79, and 2.59 times more than those who didn’t have these problems, respectively. who experienced a decrease in sleep, who experienced an increase in sleep, and who did not wake up feeling rested experienced depressive symptoms 1.61, 3.22, 3.53, and 2.59 times more, respectively, than those who did not have insomnia, who did not experience a change in sleep habits in pregnancy, and who woke up feeling rested, respectively.Conclusion: This study determined that there is a relationship between insomnia and depressive symptoms and that pregnant women experiencing insomnia presented with more depressive symptoms.Keywords: Depressions, last trimester, pregnancy, sleep characteristics.

scholarly journals The network structure of depressive symptomatology in Peruvian adults with arterial hypertension

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 19
Author(s):  
Cristian Ramos-Vera ◽  
Jonatan Banos-Chaparro ◽  
Roseline Oluwaseun Ogundokun
Keyword(s):  
Depressive Symptoms ◽  
Network Analysis ◽  
Arterial Hypertension ◽  
Network Structure ◽  
Depressive Symptomatology ◽  
Comprehensive Evaluation ◽  
Scientific Evidence ◽  
National Level ◽  
Depressive Mood ◽  
Cross Sectional

Background: Globally, arterial hypertension (AH) has increased by 90% over the last four decades, and has increased by 1.6% in Peru over the previous four years. Scientific evidence indicates the prevalence of depressive symptoms in patients with AH and its importance in the comprehensive evaluation of the adult for adherence to clinical treatment. Previous studies carried out in the Peruvian population with AH mostly report the prevalence and associations, but do not indicate which depressive symptoms are more relevant in patients with AH. This study involved a network analysis of depressive symptomatology in Peruvian patients with AH using network estimation. Network analysis is used in this study for analysis, control, and monitoring purposes. Method: A representative cross-sectional study at the national level, using secondary data from 2019 Demographic and Family Health Survey (ENDES) was performed. The sample used included men and women of age over 17 years diagnosed with AH and was able to respond to Patient Health Questionnaire-9 (PHQ-9). Results: The symptoms of depressive mood (bridging force and centrality) and energy fatigue or loss (bridge centrality) play an essential role in the network structure, as does the feeling of uselessness in terms of closeness and intermediation. Conclusion: The study highlighted the symptoms related to depressive mood and energy fatigue or loss as bridging symptoms, which could trigger a depressive episode in patients diagnosed with AH. The results will contribute to developing personalized treatments aimed at patients with specific depressive symptoms who have also been diagnosed with AH. The study analysis presents statistical coefficients of effect size (≤ 0,1 = small; > 0,1 to < 0,5 = moderate; ≥ 0,5 = large) to determine network connections.

scholarly journals Network analysis of depressive symptoms in Hong Kong residents during the COVID-19 pandemic

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Teris Cheung ◽  
Yu Jin ◽  
Simon Lam ◽  
Zhaohui Su ◽  
Brian J. Hall ◽  
...  
Keyword(s):  
Hong Kong ◽  
Depressive Symptoms ◽  
Depressive Symptom ◽  
Network Structure ◽  
Network Stability ◽  
Patient Health ◽  
Males And Females ◽  
Sad Mood ◽  
Global Strength ◽  
Community Adult

AbstractIn network theory depression is conceptualized as a complex network of individual symptoms that influence each other, and central symptoms in the network have the greatest impact on other symptoms. Clinical features of depression are largely determined by sociocultural context. No previous study examined the network structure of depressive symptoms in Hong Kong residents. The aim of this study was to characterize the depressive symptom network structure in a community adult sample in Hong Kong during the COVID-19 pandemic. A total of 11,072 participants were recruited between 24 March and 20 April 2020. Depressive symptoms were measured using the Patient Health Questionnaire-9. The network structure of depressive symptoms was characterized, and indices of “strength”, “betweenness”, and “closeness” were used to identify symptoms central to the network. Network stability was examined using a case-dropping bootstrap procedure. Guilt, Sad Mood, and Energy symptoms had the highest centrality values. In contrast, Concentration, Suicide, and Sleep had lower centrality values. There were no significant differences in network global strength (p = 0.259), distribution of edge weights (p = 0.73) and individual edge weights (all p values > 0.05 after Holm–Bonferroni corrections) between males and females. Guilt, Sad Mood, and Energy symptoms were central in the depressive symptom network. These central symptoms may be targets for focused treatments and future psychological and neurobiological research to gain novel insight into depression.

Coping Style as a Mediator of the Relationship Between Depressive Symptoms and Deliberate Self-Harm

Crisis ◽  
2011 ◽  
Vol 32 (5) ◽  
pp. 272-279 ◽  
Author(s):  
Allison S. Christian ◽  
Kristen M. McCabe
Keyword(s):  
Depressive Symptoms ◽  
Undergraduate Students ◽  
Cross Sectional Study ◽  
Self Report ◽  
Hierarchical Regression ◽  
Cross Sectional ◽  
Deliberate Self Harm ◽  
Self Blame ◽  
Self Harm ◽  
The Relationship

Background: Deliberate self-harm (DSH) occurs with high frequency among clinical and nonclinical youth populations. Although depression has been consistently linked with the behavior, not all depressed individuals engage in DSH. Aims: The current study examined maladaptive coping strategies (i.e., self-blame, distancing, and self-isolation) as mediators between depression and DSH among undergraduate students. Methods: 202 students from undergraduate psychology courses at a private university in Southern California (77.7% women) completed anonymous self-report measures. Results: A hierarchical regression model found no differences in DSH history across demographic variables. Among coping variables, self-isolation alone was significantly related to DSH. A full meditational model was supported: Depressive symptoms were significantly related to DSH, but adding self-isolation to the model rendered the relationship nonsignificant. Limitations: The cross-sectional study design prevents determination of whether a casual relation exists between self-isolation and DSH, and obscures the direction of that relationship. Conclusions: Results suggest targeting self-isolation as a means of DSH prevention and intervention among nonclinical, youth populations.

scholarly journals Tired, Worried and Burned Out, but Still Resilient: A Cross-Sectional Study of Mental Health Workers in the UK during the COVID-19 Pandemic

2021 ◽  
Vol 18 (9) ◽  
pp. 4457
Author(s):  
Sofia Pappa ◽  
Joshua Barnett ◽  
Ines Berges ◽  
Nikolaos Sakkas
Keyword(s):  
Mental Health ◽  
Emotional Exhaustion ◽  
Organizational Support ◽  
Sleep Problems ◽  
Health Workers ◽  
Maslach Burnout Inventory ◽  
Cross Sectional Study ◽  
Mental Health Workers ◽  
Sectional Study ◽  
Cross Sectional

The burden of the COVID-19 pandemic on health systems and the physical and mental health of healthcare workers (HCWs) has been substantial. This cross-sectional study aims to assess the effects of COVID-19 on the psychological wellbeing of mental health workers who provide care to a vulnerable patient population that have been particularly affected during this crisis. A total of 387 HCWs from across a large urban mental health service completed a self-administered questionnaire consisting of socio-demographic, lifestyle and work-based information and validated psychometric scales. Depression and anxiety were measured using the Patient Health Questionnaire (PHQ-9) and the Generalized Anxiety Disorder Scale (GAD-7), respectively; sleep problems with the Athens Insomnia Scale (AIS); burnout with the Maslach Burnout Inventory (MBI); and resilience with the Resilience Scale-14 (RS-14). Multivariable logistic regression analysis was performed to determine potential mediating factors. Prevalence of burnout was notable, with 52% recording moderate/severe in Emotional Exhaustion, 19.5% moderate/severe in Depersonalisation, and 55.5% low/moderate Personal Accomplishment. Over half of all respondents (52%) experienced sleep problems; the presence of depressive symptoms was a significant predictor of insomnia. An increase in potentially harmful lifestyle changes, such as smoking, alcohol consumption and overeating was also observed. However, high Resilience was reported by 70% of the samples and the importance of this is highlighted. Female gender was associated with increased levels of depression and emotional exhaustion while those with a history of mental health conditions were most at risk of affective symptoms, insomnia, and burnout. Overall, our study revealed considerable levels of psychological distress and maladaptive coping strategies but also resilience and satisfaction with organizational support provided. Findings can inform tailored interventions in order to mitigate vulnerability and prevent long-term psychological sequelae.

scholarly journals Psychosocial health of school-aged children during the initial COVID-19 safer-at-home school mandates in Florida: a cross-sectional study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sarah L. McKune ◽  
Daniel Acosta ◽  
Nick Diaz ◽  
Kaitlin Brittain ◽  
Diana Joyce- Beaulieu ◽  
...  
Keyword(s):  
Mental Health ◽  
Depressive Symptoms ◽  
Psychosocial Health ◽  
Cross Sectional Study ◽  
Home School ◽  
Sectional Study ◽  
Cross Sectional ◽  
School Aged Children ◽  
K 12 ◽  
At Home

Abstract Background Given the emerging literature regarding the impacts of lockdown measures on mental health, this study aims to describe the psychosocial health of school-aged children and adolescents during the COVID-19 Safer-at-Home School mandates. Methods A cross-sectional study was conducted in April 2020 (n = 280) among K-12 students at a research school in North Central Florida. Bivariate analysis and logistic and multinomial logistic regression models were used to examine socio-demographic and knowledge, attitude, and practice (KAP) predictors of indicators of anxiety-related, depressive, and obsessive-compulsive disorder(OCD)-related symptoms. Outcomes (anxiety, OCD, and depressive related symptoms) were measured by indices generated based on reported symptoms associated with each psychosocial outcome. Results Loss of household income was associated with increased risk for all three index-based outcomes: depressive symptoms [aOR = 3.130, 95% CI = (1.41–6.97)], anxiety-related symptoms [aOR = 2.531, 95%CI = (1.154–5.551)], and OCD-related symptoms [aOR = 2.90, 95%CI = (1.32–6.36)]. Being female was associated with being at higher risk for depressive symptoms [aOR = 1.72, 95% CI = (1.02–2.93)], anxiety-related symptoms [aOR = 1.75, 95% CI = (1.04–2.97)], and OCD-related symptoms [aOR = 1.764, 95%CI = (1.027–3.028)]. Parental practices protective against COVID-19 were associated with children being at higher risk of depressive symptoms [aOR = 1.55, 95% CI = (1.04–2.31)]. Lower school level was associated with children being at higher risk of anxiety-related and OCD-related symptoms. Conclusions As the COVID-19 pandemic continues, schools should prioritize mental health interventions that target younger, female students, and children of families with income loss. Limiting the spread of COVID-19 through school closure may exacerbate negative psychosocial health outcomes in children, thus school administrators should move quickly to target those at greatest risk.

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