Anxiety, depression, and the suicidal spectrum: a latent class analysis of overlapping and distinctive features

Investigating the association between Work Family Conflicts (WFC) and suicidal ideation in an Australian community-based cohort study

BACKGROUND

Suicidal ideation, a significant public health issue, necessitates further investigation of its correlates and precursors. Extensive research highlights the association between Work Family Conflicts (WFC) and psychological distress, including depression. However, research examining the correlation between high WFC experiences and suicidal ideation is sparse. This study explores the association between WFC and suicidal ideation within an occupation non-specific community sample.

METHODS

Community-based, representative data from the Australian-based Personality and Total Health (PATH) Through Life project formed the basis of this study. Participants eligible for the study (N = 1312) were employed either full-time or part-time and took part in an online questionnaire. Importantly, the data include robust measures of WFC, active suicidal ideation, and depression.

RESULTS

After adjusting for psychosocial job characteristics, history of suicidal ideation, and other socio-demographic factors, high WFC was associated with increased odds of active suicidal ideation (Model 4: OR: 1.58, CI: 1.04-2.40). Further, supplementary analyses indicated that depression is an important component of this relationship. Analyses exploring an interaction effect by gender showed that while a significant association between high WFC and suicidality was observed among men after adjustment for all covariates, this association was not evident for women.

LIMITATIONS

A small number of participants reported suicidal ideation, potentially affecting the statistical power to detect significant effects. WFC was measured at one time-point, prohibiting the exploration of its causal and/or chronic impact on suicidal ideation.

CONCLUSION

We find evidence that high WFC is linked to increased active suicidal ideation - specifically for men.

Latent groups from multidimensional factors and effects on suicidal ideation in older adults

BACKGROUND

Suicide is a serious social problem among older adults. However, little is known about how multidimensional factors affect suicide of older adults.

AIMS

We classify the multidimensional suicidal risk types of older adults based on their characteristics and identify differences in suicidal ideation.

METHOD

Data were obtained via a nationwide online survey targeting 612 older adults over the age of 55 years. A latent profile analysis identified three profiles, one of which represented the optimal situation for these adults.

RESULTS

We identified three distinct multidimensional suicidal risk types in older adults: high-risk predicament (24.5%), moderate-risk predicament (57.7%) and abundant internal/external resources (17.8%). In particular, depression, a major risk factor for suicide, was found together with self-neglect in each group. Multiple regression analysis showed that older adults in the moderate-risk predicament and high-risk predicament groups were more likely to have suicidal ideation than those in the abundant internal/external resources group.

CONCLUSIONS

Our findings suggest that co-occurrence of depression and self-neglect represents a suicide risk pattern in high-risk older individuals. Therefore, local communities need to urgently screen and provide interventions for such older adults and strengthen their capacity for multidimensional aspects of life to prevent suicide in the long term.

Symptoms and prevalence of common mental disorders in a heterogenous outpatient sample: an investigation of clinical characteristics and latent subgroups

BACKGROUND

Patient-reported outcome measures (PROM) provide clinicians with information about patients' perceptions of distress. When linked with treatment and diagnostic registers, new information on common mental health disorders (CMHD) and service use, may be obtained, which might be useful clinically and for policy decision-making. This study reports the prevalence of CMHD and their association with PROM severity. Further, subgroups of self-reported symptoms of depression and anxiety were examined, and their association with clinician-assessed mental disorders, functional impairment, and service use.

METHODS

In a cohort study of 2473 (63% female) outpatients, CMHD was examined with pre-treatment scores of self-reported depression and anxiety, and the number of assessments and psychotherapy appointments one year after treatment start. Factor mixture modelling (FMM) of anxiety and depression was used to examine latent subgroups.

RESULTS

Overall, 22% of patients with a CMHD had an additional comorbid mood/anxiety disorder, making the prevalence lower than expected. This comorbid group reported higher symptoms of anxiety and depression compared to patients with non-comorbid disorders. FMM revealed three classes: "anxiety and somatic depression" (33%), "mixed depression and anxiety" (40%), and "cognitive depression" (27%). The anxiety and somatic depression class was associated with older age, being single and on sick leave, higher probability of depressive-, anxiety-, and comorbid disorders, having more appointments and higher functional impairment. Although the cognitive depression class had less somatic distress than the mixed depression and anxiety class, they reported more functional impairment and had higher service use.

CONCLUSION

The results show that higher levels of somatic symptoms of depression could both indicate higher and lower levels of functional impairment and service use. A group of patients with high somatic depression and anxiety was identified, with severe impairment and high service needs. By gaining insights into CMHD factors' relation with clinical covariates, self-reported risk factors of depression and anxiety could be identified for groups with different levels of aggravating life circumstances, with corresponding service needs. These could be important symptom targets in different groups of patients.

Systematic reviews and meta-analyses on major depressive disorder: a bibliometric perspective

Background

There is a vast amount of evidence-based medicine research on the major depressive disorder (MDD) available in the literature, however, no studies on the overall performance, productivity and impact of such research have been published to date. This study explored and mapped the research outputs of MDD-related systematic reviews and meta-analyses (SR/MA) from a bibliometric perspective.

Methods

Relevant data were retrieved with search terms on MDD, systematic review and meta-analysis.

Results

A total of 4,870 papers with 365,402 citations published from 1983 to 2022 were included in the analysis. The publication output has grown steadily over time with the most publications originating from the USA (1,020; 20.94%), the UK (516; 10.60%) and China (448; 9.20%). The research collaborations between countries were most frequent between the USA and UK (266; 5.46%). Journal of Affective Disorders (379; 7.78%) was the most productive journal, while Cuijpers P was the most productive author (121; 2.48%), and University of Toronto (569; 11.78%) was the most productive institution. The top 10 most cited articles on MDD-related SR/MA had citations ranging from 1,806 to 3,448. The high-frequency keywords were mainly clustered into four themes, including psychiatric comorbidities, clinical trials, treatment, and brain stimulation in MDD.

Conclusion

The rapid increase in the number of SR/MA of MDD in recent years highlights the importance of this research field. Psychiatric comorbidities, clinical interventions, and treatment of MDD have been identified as hot topics, while biological mechanisms in MDD are likely to be an emerging research priority.

Association between the number of hours of sleep during weekdays and suicidality among Korean adolescents: Mediating role of depressive and anxiety symptoms

BACKGROUND

Adolescent suicide is a serious concern worldwide. Sleep problems are a risk factor for suicide. Therefore, the aim of this study was to evaluate associations between sleep duration and suicidal ideation/suicide attempts and determine the extent to which depressive and anxiety symptoms mediate these associations.

METHODS

Data from 54,948 middle and high school students in South Korea were collected by the stratified cluster method through the Korea Youth Risk Behavior Web-based Survey.

RESULTS

The weighted prevalences of short and long sleep durations were 19.5 % (95 % confidence interval [CI] = 18.9-20.2) and 4.6 % (95 % CI = 4.3-4.8), respectively. Short sleep duration (<5 h/day) increased the odds of suicidal ideation and suicide attempts by 1.43 (95 % CI = 1.29-1.58) and 1.78 (95 % CI = 1.41-2.25), respectively. Long sleep duration (>9 h/day) increased the odds of suicide attempts by 1.5 (95 % CI = 1.02-2.21). Depressive and anxiety symptoms significantly mediated the relationship between sleep duration and suicidal intensity with a satisfactory goodness of fit.

LIMITATIONS

Causal relationships could not be examined due to the cross-sectional study design. Information on other psychopathologies, besides depression and anxiety, was unavailable.

CONCLUSIONS

Short sleep duration was associated with suicidal ideation and suicide attempts among Korean adolescents. Long sleep duration was associated with suicide attempts only. Both depressive and anxiety symptoms mediated the association between sleep duration and suicidal intensity; therefore, both sleep hour restoration and treatment of depressive/anxiety symptoms should be the goals of suicide prevention strategies.

Affect labeling: The role of timing and intensity

A growing number of studies have shown that labeling negative feelings can down-regulate distress. The present study aimed to test the effectiveness of affect labeling while manipulating two factors known to influence the emotion regulation process, namely timing, and emotional intensity. In Experiment 1, sixty-three participants completed a performance-based affect labeling paradigm in which they had to choose between two labels that best describe their feeling. Participants were randomly assigned to one of three experimental conditions: (1) Simultaneous labeling- the labeling occurs while watching the aversive picture. (2) Subsequent labeling- the labeling occurs immediately after watching the aversive picture. (3) Delayed labeling- the labeling occurs 10 seconds after watching the aversive picture. We found that affect labeling efficiently down-regulated distress independent of the labeling timing. In Experiment 2, seventy-nine participants utilized simultaneous labeling for aversive pictures with low and high intensity. We revealed that while affect labeling reduces distress in high-intensity aversive conditions, it increases distress in low-intensity conditions. The results question the standard advice, which calls to count to 10 before you speak in highly aversive states. In addition, it suggests that affect labeling can be beneficial in high-intensity conditions. However, it should be used with caution in low-intensity conditions.

Psychopathological Determinants of Quality of Life in People with Borderline Personality Disorder

BACKGROUND

Subjective quality of life (SQOL) in people with borderline personality disorder (BPD) is a marker of disease burden; a crucial treatment outcome; an indicator of psychosocial functioning; and a measure of interventions' effectiveness. Given the dearth of consolidated data, the current study examined psychopathological determinants of global and domain-specific SQOL in people with BPD.

METHODS

Hierarchical regression models were employed to examine in BPD patients (n = 150) the relationships of the number of BPD diagnostic criteria; the co-occurrence of other personality disorders (PDs); depression; state and trait anxiety; suicidality; self-harming; alcohol and substance use disorders with SQOL indices, namely physical health, psychological health, social relationships, environment, overall QOL and overall health. SQOL was estimated using the WHOQOL-BREF instrument.

RESULTS

Co-existing symptomatology such as depression, state and trait anxiety, and personality pathology, namely the co-occurrence of other PDs, exhibited significant associations with global and domain-specific SQOL, albeit depression was the strongest determinant of the most SQOL domains. In contrast, the number of BPD diagnostic criteria and central illness features such as suicidality, self-harming behaviour, and impulsivity manifested through alcohol and substance use did not exhibit significant associations with any SQOL dimension.

CONCLUSIONS

Comprehensive assessment of depressive symptoms should be regularly implemented in BPD services to facilitate early detection and treatment, thereby ensuring patients' SQOL. Accordingly, tackling anxiety and other PDs co-occurrence through appropriate interventions can facilitate more effectively SQOL improvement. Our findings can be explained by the hypothesis that co-existing psychopathology such as depression, anxiety and co-occurrence of other PDs in BPD patients represent illness severity indices rather than comorbid disorders, and might fully mediate the effect of BPD traits on SQOL. Future mediation analysis is required to elucidate this hypothesis.

Application of the RDoC Framework to Predict Alcohol Use and Suicidal Thoughts and Behaviors among Early Adolescents in the Adolescent Brain and Cognitive Development (ABCD) Study

Alcohol use confers risk for suicidal thoughts and behaviors (ideation, attempt) in early adolescents. The Research Domain Criteria provides a framework for examination of multidimensional and modifiable risk factors. We examined distinct latent profiles based on patterns of positive valence (reward responsivity) and cognitive systems (neurocognition) from the ABCD Study (age 9−10, N = 10,414) at baseline enrollment. Longitudinal associations were determined between baseline positive valence and cognitive profiles and group classification (alcohol use, suicidal thoughts and behaviors, or their co-occurrence) two-years after initial assessment (ages 11−12). Three unique profiles of positive valence, cognition, alcohol use, and suicidal thoughts and behaviors were identified. Two baseline profiles predicted alcohol use and suicidal thoughts and behaviors, two-years after initial assessment. Low positive valence with high cognition (but low impulsivity) predicted alcohol use (OR = 1.414, p< 0.001), while high positive valence with low cognition (but high impulsivity) predicted suicidal thoughts and behaviors (OR = 1.25, p = 0.038), compared to average positive valence and cognition. Unique profiles of positive valence and cognitive systems among 9−12-year-olds may be predictive of alcohol use and suicidal thoughts and behaviors over a two-year period. Findings underscore the potential for trajectory research on positive valence and cognitive profiles to enhance prevention for early-adolescents.

Hopelessness in Police Officers and Its Association with Depression and Burnout: A Pilot Study

Hopelessness is a particularly critical condition and a risk factor for suicide. Many studies have reported that this condition is common in some occupations and is associated with high stress that is not properly managed. This study examined the prevalence of hopeless status (HS) in a sample of police officers (POs) and the association of hopelessness with depression, burnout, and suicidality. In total, 127 out of 231 POs participated in the survey; they were assessed with the Beck Hopelessness Scale, the Beck Depression Scale, and the Maslach Burnout Inventory. A total of 26.5% of POs reported hopelessness, and a significant association was found with depression and burnout; in individual cases, these conditions were associated with suicidal thoughts. In a multivariate logistic regression model adjusted for confounding variables, depression, emotional exhaustion, and reduction of personal accomplishment were significantly associated with HP status. Depression (OR = 3.02, 95% CI: 1–9.12) and emotional exhaustion (OR = 1.88, 95% CI: 1.06–3.32) significantly increased the risk of hopelessness, while personal accomplishment (OR = 0.57, 95% CI: 0.32–1) was a protective factor. Hopelessness appears to be a very important factor to consider when assessing POs’ mental health.

Impairments of Social Interaction in Depressive Disorder

OBJECTIVE

Despite the numerous findings on the altered emotion recognition and dysfunctional social interaction behavior of depressive patients, a lot of the relationships are not clearly clarified.

METHODS

In this pilot study, 20 depressive patients (mean±SD, 38.4±14.2) and 20 healthy subjects (mean±SD, 38.9±15.3) (each in dyads) were videographed. We then analyzed their social interaction behavior and emotion processing in terms of emotion recognition, their own emotional experience, and the expression of emotions under the conditions of a semi-structured experimental paradigm.

RESULTS

Patients showed more significant impairment regarding the dimensions of social interaction behavior (i.e., attention, interest, and activity) and their interaction behavior was characterized by neutral affectivity, silence, and avoidance of direct eye contact. This interactive behavioral style was statistically related to depressive psychopathology. There were no differences concerning emotion recognition.

CONCLUSION

Impairments of non-verbal and verbal social interaction behavior of depressive patients seem to be less associated with disturbances of basic skills of emotion recognition.

Latent class analysis of depression and anxiety among medical students during COVID-19 epidemic

OBJECTIVE

The novel coronavirus disease 2019 (COVID-19) is a global public health emergency that has caused worldwide concern. The mental health of medical students under the COVID-19 epidemic has attracted much attention. This study aims to identify subgroups of medical students based on depression and anxiety and explore the influencing factors during the COVID-19 epidemic in China.

METHODS

A total of 29,663 medical students were recruited during the epidemic of COVID-19 in China. Depression and anxiety symptoms were assessed using Patient Health Questionnaire 9 (PHQ9) and Generalized Anxiety Disorder 7 (GAD7) respectively. Latent class analysis was performed based on depression and anxiety symptoms in medical students. The latent class subtypes were compared using the chi-square test. Multinomial logistic regression was used to examine associations between identified classes and related factors.

RESULTS

In this study, three distinct subgroups were identified, namely, the poor mental health group, the mild mental health group and the low symptoms group. The number of medical students in each class is 4325, 9321 and 16,017 respectively. The multinomial logistic regression results showed that compared with the low symptoms group, the factors influencing depression and anxiety in the poor mental health group and mild mental health group were sex, educational level, drinking, individual psychiatric disorders, family psychiatric disorders, knowledge of COVID-19, fear of being infected, and participate in mental health education on COVID-19.

CONCLUSIONS

Our findings suggested that latent class analysis can be used to categorize different medical students according to their depression and anxiety symptoms during the outbreak of COVID-19. The main factors influencing the poor mental health group and the mild mental health group are basic demographic characteristics, disease history, COVID-19 related factors and behavioural lifestyle. School administrative departments can carry out targeted psychological counseling according to different subgroups to promote the physical and mental health of medical students.

Predicting Suicidal Behavior Without Asking About Suicidal Ideation: Machine Learning and the Role of Borderline Personality Disorder Criteria

OBJECTIVE

Identifying predictors contributing to suicide risk could help prevent suicides via targeted interventions. However, using only known risk factors may not yield accurate enough results. Furthermore, risk models typically rely on suicidal ideation, even though people often withhold this information.

METHOD

This study examined the contribution of various predictors to the accuracy of six machine learning models for identifying suicidal behavior in a prison population (n = 353), including borderline personality disorder (BPD) and antisocial personality disorder (APD) criteria, and compared how excluding data about suicidal ideation affects accuracy.

RESULTS

Results revealed that gradient tree boosting accurately identified individuals with suicidal behavior, even without relying on questions about suicidal ideation (AUC = 0.875, F1 = 0.846). Furthermore, the model maintained this accuracy with only 29 predictors. Meeting five or more diagnostic criteria of BPD was an important risk factor for suicidal behavior. APD criteria, in the presence of other predictors, did not substantially improve accuracy. Additionally, it may be possible to implement a decision tree model to assess individuals at risk of suicide, without focusing upon suicidal ideation.

CONCLUSIONS

These findings highlight that modern classification algorithms do not necessarily require information about suicidal ideation for modeling suicide and self-harm behavior.

Emotions of COVID-19: Content Analysis of Self-Reported Information Using Artificial Intelligence

Background

The COVID-19 pandemic has disrupted human societies around the world. This public health emergency was followed by a significant loss of human life; the ensuing social restrictions led to loss of employment, lack of interactions, and burgeoning psychological distress. As physical distancing regulations were introduced to manage outbreaks, individuals, groups, and communities engaged extensively on social media to express their thoughts and emotions. This internet-mediated communication of self-reported information encapsulates the emotional health and mental well-being of all individuals impacted by the pandemic.

Objective

This research aims to investigate the human emotions related to the COVID-19 pandemic expressed on social media over time, using an artificial intelligence (AI) framework.

Methods

Our study explores emotion classifications, intensities, transitions, and profiles, as well as alignment to key themes and topics, across the four stages of the pandemic: declaration of a global health crisis (ie, prepandemic), the first lockdown, easing of restrictions, and the second lockdown. This study employs an AI framework comprised of natural language processing, word embeddings, Markov models, and the growing self-organizing map algorithm, which are collectively used to investigate social media conversations. The investigation was carried out using 73,000 public Twitter conversations posted by users in Australia from January to September 2020.

Results

The outcomes of this study enabled us to analyze and visualize different emotions and related concerns that were expressed and reflected on social media during the COVID-19 pandemic, which could be used to gain insights into citizens’ mental health. First, the topic analysis showed the diverse as well as common concerns people had expressed during the four stages of the pandemic. It was noted that personal-level concerns expressed on social media had escalated to broader concerns over time. Second, the emotion intensity and emotion state transitions showed that fear and sadness emotions were more prominently expressed at first; however, emotions transitioned into anger and disgust over time. Negative emotions, except for sadness, were significantly higher (P<.05) in the second lockdown, showing increased frustration. Temporal emotion analysis was conducted by modeling the emotion state changes across the four stages of the pandemic, which demonstrated how different emotions emerged and shifted over time. Third, the concerns expressed by social media users were categorized into profiles, where differences could be seen between the first and second lockdown profiles.

Conclusions

This study showed that the diverse emotions and concerns that were expressed and recorded on social media during the COVID-19 pandemic reflected the mental health of the general public. While this study established the use of social media to discover informed insights during a time when physical communication was impossible, the outcomes could also contribute toward postpandemic recovery and understanding psychological impact via emotion changes, and they could potentially inform health care decision making. This study exploited AI and social media to enhance our understanding of human behaviors in global emergencies, which could lead to improved planning and policy making for future crises.

Prevalence and correlates of major depressive disorder: a systematic review

OBJECTIVES

Major depressive disorder (MDD) is one of the most disabling mental illnesses and it has a significant impact on society. This review aims to provide updated scientific evidence about the epidemiology of MDD.

METHODS

A systematic literature review of the PubMed and MEDLINE databases was performed to identify articles on the prevalence of MDD and its correlates. The search was restricted to manuscripts published between January 2001 and December 2018.

RESULTS

Sixty-three articles were included in the review. The lifetime prevalence of MDD ranged from 2 to 21%, with the highest rates found in some European countries and the lowest in some Asian countries. The main sociodemographic correlates were separated/divorced marital status and female gender. Child abuse, intimate partner violence, and comorbidity with other physical and mental disorders also were consistently associated with MDD across the reviewed studies.

CONCLUSIONS

MDD is a highly prevalent condition worldwide. There are remarkable interregional differences in the disorder's prevalence, as well as in certain sociodemographic correlates. MDD is also highly comorbid with physical and mental health problems.

Suicidal Ideation and Insomnia in Bipolar Disorders: Idéation suicidaire et insomnie dans les troubles bipolaires

OBJECTIVE

Bipolar disorder (BD) confers elevated suicide risk and associates with misaligned circadian rhythm. Real-time monitoring of objectively measured sleep is a novel approach to detect and prevent suicidal behavior. We aimed at understanding associations between subjective insomnia and actigraphy data with severity of suicidal ideation in BDs.

METHODS

This prospective cohort study comprised 76 outpatients with a BD aged 18 to 65 inclusively. Main measures included 10 consecutive days of wrist actigraphy; the Athens Insomnia Scale (AIS); the Montgomery-Åsberg Depression Rating Scale (MADRS); the Quick Inventory of Depressive Symptoms-16, self-rating (QIDS-SR-16); and the Columbia Suicide Severity Rating Scale. Diagnoses, medications, and suicide attempts were obtained from chart review.

RESULTS

Suicidal ideation correlated moderately with subjective insomnia (AIS with QIDS-SR-16 item 12 ρ =0.26, P = 0.03; MADRS item 10 ρ = 0.33, P = 0.003). Graphical sleep patterns showed that suicidal patients were enriched among the most fragmented sleep patterns, and this was confirmed by correlations of suicidal ideation with actigraphy data at 2 visits. Patients with lifetime suicide attempts (n = 8) had more varied objective sleep (a higher standard deviation of center of daily inactivity [0.64 vs. 0.26, P = 0.01], consolidation of daily inactivity [0.18 vs. 0.10, P = <0.001], sleep offset [3.02 hours vs. 1.90 hours, P = <0.001], and total sleep [105 vs. 69 minutes, P = 0.02], and a lower consolidation of daily inactivity [0.65 vs. 0.79, P = 0.03]).

CONCLUSIONS

Subjective insomnia, a nonstigmatized symptom, can complement suicidality screens. Longer follow-ups and larger samples are warranted to understand whether real-time sleep monitoring predicts suicidal ideation in patient subgroups or individually.

A study on classification features of depressive symptoms in adolescents

Although extensive literature has addressed depression among adolescents, few studies have emphasized the classification features of depressive symptoms in adolescents. To gain insight into the hierarchy and heterogeneity of depression in adolescents based on symptoms, 5086 adolescents completed the Chinese version of the Center for Epidemiological Studies Depression Scale (CES-D). Using Latent Class Analysis (LCA), we identified different subgroups of adolescents based on depressive symptoms. Multivariate logistic regression analysis was implemented to examine the relations between latent classes and demographic covariates. Four latent classes of individuals with depressive symptoms displaying a pattern of hierarchical organization were identified. The four classes were ordered by the degree of severity, ranging from the students reporting the highest number of depressive symptoms to the lowest number: "probable clinical depression", "subthreshold depression", "mild depression" and "low depression", accounting for 8.2%, 19.2%, 41.8% and 30.8% of total sample respectively. Further analyses revealed that compared to the "mild depression" class, the rest of three classes differed significantly across age groups and only child (vs. sibling) status. In conclusion, classifying the groups of adolescents based on features of depressive symptoms is potentially useful for understanding risk factors and developing tailored prevention and intervention programs for this age group.

Understanding self-harm in older adults: A qualitative study

BACKGROUND

Self-harm is the leading risk factor for suicide, with elevated rates reported amongst older populations. This study explores how older adults experience self-harm, identifying factors leading to self-harm.

METHODS

Semi-structured interviews with older adults (≥ 60 years) engaging in self-harm and support workers from third sector services in England. Older adults were invited to participate in a follow-up interview. Interviews were recorded, transcribed verbatim and data analysed thematically. Ethical approval obtained from Keele University's Ethics Review Panel. A Patient Involvement group contributed to study design, data analysis and interpretation.

OUTCOMES

Between September 2017 to September 2018, 24 interviews were conducted involving 16 participants: nine older adults and seven support workers. Eight older adults consented to follow-up interviews. All older adults reported diagnoses of mental illness in addition to physical illness. Participants identified diverse stressors accumulating over the life-course leaving older adults particularly vulnerable to self-harm. Such stressors included adverse events, loss, interpersonal and health problems. A sense of shame and stigma amongst older people using self-harm to manage distress was also reported.

INTERPRETATION

Self-harm is often concealed due to stigma and shame, being further accentuated amongst older adults, which may result in low levels of medical help-seeking behaviour for self-harm. Self-harm occurred along a spectrum of no-suicidal intent to high-levels of intent, suggesting self-harm holds different functions to older adults. Clinicians should be aware of the existence of self-harm in this age-group, and the heightened risk amongst those with comorbidities so adequate assessment, support and/or referral is provided.

Anxiety sensitivity and suicidal ideation/suicide risk: A meta-analysis

OBJECTIVE

Suicide is a global public health concern. To inform the prevention and treatment of suicidality, it is crucial to identify transdiagnostic vulnerability factors for suicide and suicide-related conditions. One candidate factor is anxiety sensitivity (AS)-the fear of anxiety-related sensations-which has been implicated in the pathogenesis of a host of mental health outcomes, including suicidal thoughts and behaviors. Importantly, AS is distinct from trait anxiety and negative affectivity, highlighting its potential incremental utility in the understanding of psychopathology. Despite a burgeoning body of literature demonstrating that AS is linked to suicidal thoughts and behaviors, this research has yet to be synthesized.

METHOD

This meta-analysis includes 33 articles representing 34 nonredundant samples (N = 14,002) that examined at least one relationship between AS global or subfactor (i.e., cognitive, physical, social) scores and suicidal ideation and/or suicide risk.

RESULTS

Findings revealed small-to-moderate and moderate associations between global AS and suicidal ideation (r = .24, 95% confidence interval (CI): [.21, .26], p < .001) and suicide risk (r = .35, 95% CI [.31, .38], p < .001), respectively. All AS subfactors evinced significant associations with suicidal ideation (rs = .13-.24) and suicide risk (rs = .22-.32).

CONCLUSIONS

AS is related to suicidal ideation and global suicide risk. Research is needed to disentangle AS from other indices of distress in the prediction of suicidal thoughts and behaviors. Theoretical and clinical implications of these findings are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Anxiety and depression: toward overlapping and distinctive features

This Special Issue of Cognition and Emotion addresses one of the cardinal concerns of affective science, which is overlapping and distinctive features of anxiety and depression. A central finding in the study of anxiety and depression is that they are moderately highly correlated with each other. This leads us to the question: What is behind this co-occurrence? Possible explanations relate to poor discriminant validity of measures; both emotional states are associated with negative affect; stressful life events; impaired cognitive processes; they share a common biological/genetic diathesis. However, despite a set of common (nonspecific) features, anxiety and depression are clearly not identical emotional states. Differences between them might be best viewed, for example, through their heterogeneous and multi-layered nature, adaptive functions and relations with regulatory processes, positive affect, and motivation or complex cognitive processes. In this introduction we consider several approaches (e.g. functional approach; tripartite model and content-specificity hypothesis) to which most research in this Special Issue is relevant. In addition, we have asked contributors to this Special Issue to indicate how their own studies on comparisons between anxiety and depression and models on anxiety and depression move this area of research to more mature science with applicability.