Behavioral empathy failures and suicidal behavior

The effects of psychological interventions on suicide for cancer patients: a systematic review and network meta-analysis

Numerous psychological interventions are available for suicidal and death ideation (SDI) and suicidal behavior among cancer patients. To identify the optimal psychological interventions for reducing SDI and suicidal behavior in cancer patients. However, it remains unclear which psychological intervention is the most effective. We performed a pairwise and network meta-analysis by searching seven databases from the date of inception until 8 April 2022. An important focus of this network meta-analysis was the comparison of the effects of various psychological interventions on the reduction of SDI and suicidal behavior among cancer patients. For determining efficacy, we used standardized mean differences (SMDs) and 95% confidence intervals (CIs). Besides, a pairwise meta-analysis, inconsistency test, network meta-analysis, the surface under the cumulative rankings curve (SUCRA), comparison-adjusted funnel plot, subgroup analysis, and sensitivity analysis were also carried out. A total of 8 studies involving 1,350 patients were searched in this study. It showed that empathy therapy (SUCRA = 95.3%) has the best effect among the six interventions. Comprehensive psychological intervention (SUCRA = 77.6%) was ranked in the top two positions, followed by meaning-centered therapy (SUCRA = 40.7%). Comparison-adjusted funnel plots revealed no significant publication bias. In addition, our conclusions have not changed significantly after the sensitivity analysis. In this network meta-analysis, empathy therapy was identified as the optimal choice for reducing SDI and suicidal behaviors in cancer patients. Further multi-center and high-quality RCT studies should be conducted to make our conclusion more rigorous.

Social decision-making in major depressive disorder: A three-level meta-analysis

Major Depressive Disorder (MDD) is frequently associated with social dysfunction and impaired decision-making, but its impact on social decisions remains unclear. Thus, we conducted a series of meta-analyses to examine the effects of MDD on key social decision phenomena, including trust, altruistic punishment, and cooperation. We searched Web of Science, PubMed, PsycINFO, and Embase up to December 2023, using Hedges' g to compare social decision-making between MDD patients and healthy controls (HCs). Meta-analytic results showed that MDD patients exhibited a significant reduction in trust (Hedges' g = -0.347, p < 0.001), no significant difference in altruistic punishment (Hedges' g = 0.232, p = 0.149), and an increase in cooperative behaviors (Hedges' g = 0.361, p = 0.002) compared to HCs. The moderation analysis revealed that age (p = 0.039) and region (p = 0.007) significantly moderated altruistic punishment, with older MDD patients and those from Asian and European regions having larger MDD-HC contrast than others. Regarding cooperation, moderation analysis indicated that age (p = 0.028), years of education (p = 0.054), and treatment coverage (p = 0.042) were significant moderators, indicating larger MDD-HC contrast in older, less-educated and better-treated people. These findings suggest MDD has different impacts on different social decisions, highlighting the need for fine-tuned therapeutic interventions that address these differences. The data also underscores the importance of considering demographic and treatment-related variables in managing MDD, which could inform personalized treatment strategies and improve social functionality and patient outcomes.

Leveraging Decision Science to Characterize Depression

This brief review examines the potential to use decision science to objectively characterize depression. We provide a brief overview of the existing literature examining different domains of decision-making in depression. Because this overview highlights the specific role of reinforcement learning as an important decision process affected in the disorder, we then introduce reinforcement learning modeling and explain how this approach has identified specific reinforcement learning deficits in depression. We conclude with ideas for future research at the intersection of decision science and depression, emphasizing the potential for decision science to help uncover underlying mechanisms and targets for the treatment of depression.

Longitudinal investigation of the presence of different trajectories and associated health and socio-economic determinants, for participants who report suicidal ideation within a community-based public health survey

OBJECTIVE

Given the paucity of evidence-based research investigating different suicidal ideation profiles and trajectories, this project sought to investigate health and socio-economic factors associated with the presence of suicidal ideation and changes in ideation over time.

DESIGN

Longitudinal cohort design, using logistic regression analysis.

SETTING

A public health survey was administered at two timepoints in a community setting across the North West of England. In the 2015/2016 survey, participants were recruited from high (n=20) and low (n=8) deprivation neighbourhoods. In the 2018 survey, only the 20 high-deprivation neighbourhoods were included.

PARTICIPANTS

4287 people were recruited in 2015/2016 and 3361 were recruited in 2018. The 2018 sample was subdivided into those who responded only in 2018 (n=2494: replication sample) and those who responded at both timepoints (n=867: longitudinal sample).

PRIMARY OUTCOME MEASURES

Suicide ideation was the dependent variable which was assessed using item 9 of the Patient Health Questionnaire instrument.

RESULTS

The prevalence of suicidal ideation was 11% (n=454/4319) at 2015/2016 and 16% (n=546/3361) at 2018.Replication study results highlighted: persistent debilitation from physical ill health and/or medication side effects; demographic factors (ie, middle-aged, single or never married); and personal coping strategies (ie, smoking) as risk factors for suicidal ideation. A static/improved financial position and high levels of empathy were protective factors.Longitudinal study results confirmed three suicidal ideation trajectories: 'onset', 'remission' and 'persistence'. Similar findings to the replication study were evidenced for the onset and persistence trajectories. Persistent suicidal ideation was synonymous with higher levels of practical support which may correspond to the higher levels of debilitation and functional disability reported within this group. Remission was characterised by fewer debilitating factors and higher levels of self-agency.

CONCLUSION

A greater appreciation of the heterogeneity of suicidal trajectories should lead to the implementation of broad clinical assessments and targeted interventions.

Neural responses to social decision-making in suicide attempters with mental disorders

BACKGROUND

Decision-making deficits have been reported in suicide attempters and may be a neuropsychological trait of vulnerability to suicidal behavior. However, little is known about how neural activity is altered in decision-making. This study aimed to investigate the neural responses in suicide attempters with mental disorders during social decision-making. Electroencephalography (EEG) were recorded from 52 patients with mental disorders with past suicide attempts (SAs = 26) and without past suicide attempts (NSAs = 26), as well as from 22 age- and sex- matched healthy controls (HCs) during the Ultimatum Game (UG), which is a typical paradigm to investigate the responses to fair and unfair decision-making.

METHODS

MINI 5.0 interview and self report questionnaire were used to make mental diagnosis and suicide behavior assessment for individuals. Event-related potential (ERP) and phase-amplitude coupling (PAC) were extracted to quantify the neural activity. Furthermore, Spearman correlation and logistic regression analyses were conducted to identify the risk factors of suicidal behavior.

RESULTS

ERP analysis demonstrated that SA patients had decreased P2 amplitude and prolonged P2 latency when receiving unfair offers. Moreover, SA patients exhibited greater negative-going feedback-related negativity (FRN) to unfair offers compared to fair ones, whereas such a phenomenon was absent in NSA and HC groups. These results revealed that SA patients had a stronger fairness principle and a disregard toward the cost of punishment in social decision-making. Furthermore, theta-gamma and beta-gamma PAC were involved in decision-making, with compromised neural coordination in the frontal, central, and temporal regions in SA patients, suggesting cognitive dysfunction during social interaction. Statistically significant variables were used in logistic regression analysis. The area under receiver operating characteristic curve in the logistic regression model was 0.91 for SA/HC and 0.84 for SA/NSA.

CONCLUSIONS

Our findings emphasize that suicide attempts in patients with mental disorders are associated with abnormal decision-making. P2, theta-gamma PAC, and beta-gamma PAC may be neuro-electrophysiological biomarkers associated with decision-making. These results provide neurophysiological signatures of suicidal behavior.

A Systematic Review of Behavior-Outcome Psychological Assessments as Correlates of Suicidality

AIM

Identifying correlates of suicidality is an important goal for suicide researchers because these correlates may predict suicidal behaviors. Psychological tasks that assess sensitivity to the outcomes of actions (i.e., consequence-based learning) have been commonly used by researchers seeking to identify correlates of suicidality. This is likely due to the straightforward integration of the tasks within most theoretical frameworks for understanding suicidality. Contextual factors have been shown to have a substantial effect on responding in behavior-outcome tasks. However, the direct relevance of these factors as determinants of behavior in suicide research is not clear. Thus, the purpose of this review was to assess the role of context in tasks involving behavior-outcome relations in suicide research.

METHODS

Four databases were searched using terms from general learning theory. Articles that featured evaluation of tasks with hypothetical or real outcomes to differentiate suicidality were included.

RESULTS

Eighty-two studies met inclusion criteria. Across studies there were 27 different tasks. Most instances of tasks across studies involved rewards (76.9%), while others emphasized punishment (15.7%), social (5.6%), or virtual suicide (1.8%) outcomes. Differentiation of suicidality was detected by 43.4%, 64.7%, 83.3%, and 50% of tasks featuring reward, punishment, social contexts, and virtual suicide respectively. All but five studies were retrospective.

CONCLUSION

Tasks that more closely mimic contexts and outcomes related to suicide appear to produce more pronounced differentiation of people with suicidality from people without suicidality. The lack of prospective designs is an important limitation of the literature.HIGHLIGHTSTasks that involve punishment or social outcomes better discriminate suicidality.Reward-based tasks are overused in suicide research.The conditioning hypothesis of suicidality is closely aligned with the literature.Only 5 of 82 studies incorporated prospective measures.

Theory of Mind and Suicidality: A Meta-Analysis

OBJECTIVE

Disturbances in interpersonal functioning are prevalent in individuals with suicidality. Foundational for interpersonal functioning is theory of mind (ToM), a social-cognitive ability that allows individuals to understand the thoughts and feelings of others. Recent work has begun to investigate ToM performance in individuals with suicidality, though no review has quantitatively aggregated findings from these varied studies. The current study investigated the relations between ToM and suicidality with meta-analysis.

METHOD

We identified and meta-analyzed 15 studies that presented data for 2,895 participants (617 of whom had reported at least one suicide attempt).

RESULTS

Results indicated a significant, negative relation between ToM and suicidality with a medium overall effect size (g = -.475). Moderator analyses revealed that this effect was consistent across age, sex, ToM content, and suicidal outcome.

CONCLUSION

Deficits in ToM associated with suicidality hold promise for risk-identification, treatment, and prevention work.HighlightsTheory of mind (ToM) abilities are critical for effective interpersonal functioning.Meta-analytics results indicate that ToM deficits are associated with suicidality.Identifying such suicidality-related ToM deficits may inform risk-identification, treatment, and prevention work.

Investigation to identify individual socioeconomic and health determinants of suicidal ideation using responses to a cross-sectional, community-based public health survey

OBJECTIVES

To address a gap in knowledge by simultaneously assessing a broad spectrum of individual socioeconomic and potential health determinants of suicidal ideation (SI) using validated measures in a large UK representative community sample.

DESIGN

In this cross-sectional design, participants were recruited via random area probability sampling to participate in a comprehensive public health survey. The questionnaire examined demographic, health and socioeconomic factors. Logistic regression analysis was employed to identify predictors of SI.

SETTING

Community setting from high (n=20) and low (n=8) deprivation neighbourhoods across the North West of England, UK.

PARTICIPANTS

4319 people were recruited between August 2015 and January 2016. There were 809 participants from low-deprivation neighbourhoods and 3510 from high-deprivation neighbourhoods. The sample comprised 1854 (43%) men and 2465 (57%) women.

PRIMARY OUTCOME MEASURES

SI was the dependent variable which was assessed using item 9 of the Patient Health Questionnaire-9 instrument.

RESULTS

454 (11%) participants reported having SI within the last 2 weeks. Model 1 (excluding mental health variables) identified younger age, black and minority ethnic (BME) background, lower housing quality and current smoker status as key predictors of SI. Higher self-esteem, empathy and neighbourhood belonging, alcohol abstinence and having arthritis were protective against SI. Model 2 (including mental health variables) found depression and having cancer as key health predictors for SI, while identifying as lesbian, gay, bisexual, transgender or queer (LGBTQ) and BME were significant demographic predictors. Alcohol abstinence, having arthritis and higher empathy levels were protective against SI.

CONCLUSIONS

This study suggests that it could be useful to increase community support and sense of belonging using a public health approach for vulnerable groups (e.g. those with cancer) and peer support for people who identify as LGBTQ and/or BME. Also, interventions aimed at increasing empathic functioning may prove effective for reducing SI.

Evaluation of Anxiety, Suicidal Risk, Daily Stress, Empathy, Perceived Emotional Intelligence, and Coping Strategies in a Sample of Spanish Undergraduates

Anxiety disorders and suicide are commonly under-recognized issues that can be a public health problem. Adolescents are among the most affected population groups and studying them can prevent serious health problems. These two elements are related, but at the same time, they can only be understood from a multifactorial point of view, so other related variables such as emotional intelligence, empathy, or coping strategies are key to understand their effect on the population. In this study, a series of methods to measure the variables of interest were applied to a specific group of adolescents to determine their mental health levels, focusing on suicide and anxiety episodes. The results reflected average levels with a tendency to be high in the case of anxiety and nonalarming levels in terms of suicide risk, both parameters presenting more worrying values in women. In turn, the correlation between suicide and anxiety was demonstrated considering the other variables (coping strategies, empathy, emotional intelligence, and prosociality). This research has relevant implications for the diagnosis, orientation, and design of psychoeducational and clinical interventions that contribute to the improvement of their well-being and quality of life.

Multiple Facets of Value-Based Decision Making in Major Depressive Disorder

Depression is clinically characterized by obvious changes in decision making that cause distress and impairment. Though several studies suggest impairments in depressed individuals in single tasks, there has been no systematic investigation of decision making in depression across tasks. We compare participants diagnosed with Major Depressive Disorder (MDD) (n = 64) to healthy controls (n = 64) using a comprehensive battery of nine value-based decision-making tasks which yield ten distinct measures. MDD participants performed worse on punishment (d = −0.54) and reward learning tasks (d = 0.38), expressed more pessimistic predictions regarding winning money in the study (d = −0.47) and were less willing to wait in a persistence task (d = −0.39). Performance on learning, expectation, and persistence tasks each loaded on unique dimensions in a factor analysis and punishment learning and future expectations each accounted for unique variance in predicting depressed status. Decision-making performance alone could predict depressed status out-of-sample with 72% accuracy. The findings are limited to MDD patients ranging between moderate to severe depression and the effects of medication could not be accounted for due to the cross sectional nature of the study design. These results confirm hints from single task studies that depression has the strongest effects on reinforcement learning and expectations about the future. Our results highlight the decision processes that are impacted in major depression, and whose further study could lead to a more detailed computational understanding of distinct facets of this heterogeneous disorder.

Innovations in the science of suicide

Globally, close to 800,000 individuals die by suicide each year. A scientific understanding of suicidal thoughts and behaviors have been slow to emerge owing to a number of challenges including low base rates, complexity and nonlinearity, low precision and accuracy of identification and detection methods, and variability across social and environmental contexts. To overcome these challenges, researchers have developed increasingly innovative and creative methods to overcome these challenges. These innovations hold considerable promise for advancing the science of suicide via large leaps forward rather than incremental steps. In this special issue of Behaviour Research and Therapy, we highlight several such efforts.