Maladaptive mood repair predicts suicidal behaviors among young adults with depression histories

Prevalence and predictors of suicide ideation among university and high-school students during India's 2nd wave of the COVID-19 pandemic

Student suicide ideation increased globally during the SARS-CoV-2 pandemic. There is scarce literature addressing suicide ideation during global health crises. Therefore, this study investigates prevalence and predictors of suicide ideation during India's COVID-19 Second Wave. We also examine the 3-Step Theory's assertion that both pain and hopelessness are necessary to have suicidal thoughts. Sample recruitment was through an online anonymous questionnaire. Inclusion criteria included students aged 18 or older, living in India during the time of the study (N = 535). Data collection was through the online questionnaire. Three categories of variables were investigated as potential predictors of suicide ideation: Sociodemographic (e.g., age, gender, education, economic status), COVID-19-specific (e.g., online classes, fear of virus contagion, vaccination status) and Clinical (e.g., sad mood, fear, loneliness, hopelessness). Data analysis (using SPSS-26) included descriptive statistics for describing data characteristics, Spearman Rho Correlation (assess the strength and direction of association between variables), and Binary Logistic Regression to help identify predictors of suicide ideation. Ordinal variables were measured using Likert scales with some recoded into binomial variables for the Regression analysis. Clinical variables predicted suicidal ideation, including fear of failure (OR = 4.17, 95% CI:2.51-6.94; p < .001), sleep disturbance (OR = 3.04, CI:1.67-5.52; p < .001), loneliness (OR = 2.77, CI:1.21-6.32; p < .01), sadness (O = 2.89, CI:1.59-5.32), and loss of interest (OR = 2.60, CI:1.37-4.93). Suicidal thoughts were reported by 48.7% of the student-participants. The Three-Step Theory was partially supported, as students feeling psychological pain but not hopelessness still reported suicidal ideation. Anticipating future global health crises, policy-supported mental health mitigation strategies are critically needed for youth, designed to reduce suicidal ideation, enhance resiliency, and to foster mental skills. These should enable them to successfully manage unexpected life challenges.

Modelling the Relationship Between Resilience to Depression and Recent Stressful Life Events in University Students

Resilience, or successful coping with the experience of stressful life events (SLEs), protects against depression, but its operational mechanisms are unclear. Views diverge whether resilience intervenes as a trait or as a process of dynamic interactions of protective factors, such as self-esteem, social support and family cohesion. We evaluated five theoretically-based models of how resilience, defined as either a trait or a process, interacts with recent SLEs, to explain depressive symptomatology in 2434 university students. The moderating effect of problematic, age-inappropriate parenting (i.e., helicopter parenting) was also assessed. SLEs moderated both the effects of trait and process resilience on depression, but models conceptualising resilience as a dynamic process of interacting components showed better explanatory power than models conceptualising resilience solely as a trait. Trait resilience was protective through self-esteem at all levels of SLEs exposure (low, mild, moderate or high), and significantly, but less so through hope or social support. Experiencing helicopter parenting weakened the protective influence of process resilience, through decreasing family cohesion in the presence of SLEs. The overall assessment of the five models supports a process conceptualisation of resilience to depression in the face of adversity. However, the results also suggest that not all protective factors are equally important, with self-esteem appearing a significant and strong mediator of resilience to depression in all models including it as a variable. Building process resilience is proposed as a key intervention target for depressive symptoms. Clinical assessments and interventions following SLEs should routinely consider both trait resilience and self-esteem, as the interaction of these two factors protects against depression even at the highest levels of adversity exposure. Depression prevention approaches should address the individual's experience of overparenting, given the deleterious influence of helicopter parenting on resilience.

History of major depressive disorder is associated with differences in implicit learning of emotional faces

Major depressive disorder is often associated with worsened reward learning, with blunted reward response persisting after remission. In this study, we developed a probabilistic learning task with social rewards as a learning signal. We examined the impacts of depression on social rewards (facial affect displays) as an implicit learning signal. Fifty-seven participants without a history of depression and sixty-two participants with a history of depression (current or remitted) completed a structured clinical interview and an implicit learning task with social reward. Participants underwent an open-ended interview to evaluate whether they knew the rule consciously. Linear mixed effects models revealed that participants without a history of depression learned faster and showed a stronger preference towards the positive than the negative stimulus when compared to the participants with a history of depression. In contrast, those with a history depression learned slower on average and displayed greater variability in stimulus preference. We did not detect any differences in learning between those with current and remitted depression. The results indicate that on a probabilistic social reward task, people with a history of depression exhibit slower reward learning and greater variability in their learning behavior. Improving our understanding of alterations in social reward learning and their associations with depression and anhedonia may help to develop translatable psychotherapeutic approaches for modification of maladaptive emotion regulation.

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

BACKGROUND

Anhedonia 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.

METHOD

A 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.

RESULTS

The 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.

LIMITATION

Causal relations between anhedonia and SI could not be determined due to the cross-sectional study design.

CONCLUSIONS

SI 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.

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

BACKGROUND

Persons 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.

METHODS

Adolescents 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.

RESULTS

Prevalence 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.

CONCLUSIONS

Findings 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.

Informing the study of suicidal thoughts and behaviors in distressed young adults: The use of a machine learning approach to identify neuroimaging, psychiatric, behavioral, and demographic correlates

Young adults are at high risk for suicide, yet there is limited ability to predict suicidal thoughts and behaviors. Machine learning approaches are better able to examine a large number of variables simultaneously to identify combinations of factors associated with suicidal thoughts and behaviors. The current study used LASSO regression to investigate extent to which a number of demographic, psychiatric, behavioral, and functional neuroimaging variables are associated with suicidal thoughts and behaviors during young adulthood. 78 treatment seeking young adults (ages 18-25) completed demographic, psychiatric, behavioral, and suicidality measures. Participants also completed an implicit emotion regulation functional neuroimaging paradigm. Report of recent suicidal thoughts and behaviors served as the dependent variable. Five variables were identified by the LASSO regression: Two were demographic variables (age and level of education), two were psychiatric variables (depression and general psychiatric distress), and one was a neuroimaging variable (left amygdala activity during sad faces). Amygdala function was significantly associated with suicidal thoughts and behaviors above and beyond the other factors. Findings inform the study of suicidal thoughts and behaviors among treatment seeking young adults, and also highlight the importance of investigating neurobiological markers.

Highlighting psychological pain avoidance and decision-making bias as key predictors of suicide attempt in major depressive disorder-A novel investigative approach using machine learning

OBJECTIVE

Predicting suicide is notoriously difficult and complex, but a serious public health issue. An innovative approach utilizing machine learning (ML) that incorporates features of psychological mechanisms and decision-making characteristics related to suicidality could create an improved model for identifying suicide risk in patients with major depressive disorder (MDD).

METHOD

Forty-four patients with MDD and past suicide attempts (MDD_SA, N = 44); 48 patients with MDD but without past suicide attempts (MDD_NS, N = 48-42 of whom with suicide ideation [MDD_SI, N = 42]), and healthy controls (HCs, N = 51) completed seven psychometric assessments including the Three-dimensional Psychological Pain Scale (TDPPS), and one behavioral assessment, the Balloon Analogue Risk Task (BART). Descriptive statistics, group comparisons, logistic regressions, and ML were used to explore and compare the groups and generate predictors of suicidal acts.

RESULTS

MDD_SA and MDD_NS differed in TDPPS total score, pain arousal and avoidance subscale scores, suicidal ideation scores, and relevant decision-making indicators in BART. Logistic regression tests linked suicide attempts to psychological pain avoidance and a risk decision-making indicator. The resultant key ML model distinguished MDD_SA/MDD_NS with 88.2% accuracy. The model could also distinguish MDD_SA/MDD_SI with 81.25% accuracy. The ML model using hopelessness could classify MDD_SI/HC with 94.4% accuracy.

CONCLUSION

ML analyses showed that motivation to avoid intolerable psychological pain, coupled with impaired decision-making bias toward under-valuing life's worth are highly predictive of suicide attempts. Analyses also demonstrated that suicidal ideation and attempts differed in potential mechanisms, as suicidal ideation was more related to hopelessness. ML algorithms show useful promises as a predictive instrument.

Association of parenting with suicidal ideation and attempts in children and youth: protocol for a systematic review and meta-analysis of observational studies

BACKGROUND

Suicide is a leading cause of death in children and youth, with suicidal thoughts and suicide attempts (referred to as non-fatal suicidal behaviors (NFSB)) being among its strongest predictors. Positive parenting (e.g., warmth, responsiveness), negative parenting (e.g., control, hostility), and parent-child relationship quality (e.g., trust, communication) have been reported to be associated with differences in NFSB in this population. To date, no comprehensive systematic review has considered together the wide range of parenting factors studied in relation to NFSB, and no meta-analysis of existing findings has been conducted. The present study will critically appraise and synthesize the existing evidence from observational studies that examine the relationships between parenting factors and (i) suicidal ideation and (ii) suicide attempt in children and youth.

METHODS

Studies will be retrieved from APA PsycInfo, MEDLINE, CINAHL, Embase, Scopus, and the Cochrane Library databases. Retrospective, cross-sectional, and longitudinal studies, conducted in clinical and population settings, among youth aged less than 25 years and published as articles and dissertations in English or French will be eligible. Two reviewers will select articles using the Covidence Software after title and abstract screening and full-text assessment, will extract information using double data entry, and will appraise studies' quality using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Any disagreements will be discussed with a third reviewer. Publication bias will be evaluated using funnel plots and Egger's test. In addition to a narrative summary of results, meta-analyses will be conducted using results from at least three studies. Three-level random effect models will allow to derive pooled estimates from dependent effect sizes (from the same sample or study). In case of significant heterogeneity, moderation analyses will be performed considering participants' characteristics and methodological aspects of studies. The results will be reported according to the PRISMA guidelines, and the certainty of evidence will be assessed using the GRADE approach.

DISCUSSION

In highlighting parenting factors associated with NFSB and in estimating the overall strength of these associations in children and youth, our results will inform further intervention and prevention strategies designed for young people experiencing NFSB and their families.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020165345.

Coping strategies, cyberbullying behaviors, and depression among Chinese netizens during the COVID-19 pandemic: a web-based nationwide survey

BACKGROUND

As a major life stressor now, the COVID-19 pandemic could substantially increase risks of cyberbullying and depression for global people, especially in the context of increased digital interconnectedness and strict social distancing. Though people are adopting different coping strategies, still little is known about their cyberbullying and depression and how the two associated with coping strategies.

METHODS

A web-based nationwide questionnaire survey was conducted among 5,608 netizens during the peak time of COVID-19 in China. The study collected cross-sectional data on participants' coping strategies, general cyberbullying behaviors, cyberbullying behaviors specifically to residents of Hubei Province where first COVID-19 case was reported, and depression.

RESULTS

A two-factor structure applied to participants' coping strategies, namely problem-focused coping and emotion-focused coping, and the former was more adopted. There existed gender, age, education, and income differences in the coping strategies. Problem-focused coping was associated with less cyberbullying behaviors while had no correlation with depression; emotion-focused coping was found positively correlated with cyberbullying and depression. The association between emotion-focused coping and depression was mediated by cyberbullying.

LIMITATIONS

The study used cross-sectional design, and its findings should be cautioned to be generalized to other countries, due to the differences in culture, stage of crisis, and government policies on COVID-19.

CONCLUSIONS

Problem-focused coping was associated with less cyberbullying, and emotion-focused coping predicted cyberbullying and depression. Cyberbullying mediated the correlation between emotion-focused coping and depression. These findings provide new perspectives for interventions on people's coping strategies towards COVID-19 pandemic.