Aberrant cognitive empathy in individuals with elevated social anxiety and regulation with emotional working memory training.

Social anxiety may disrupt the empathic process, and well-regulated empathy is critical for navigating the social world. Two studies aimed to further understand empathy in the context of social anxiety. Study 1 compared individuals with elevated or normative social anxiety on a measure assessing cognitive and affective empathy for positive and negative emotions conveyed by other people ("targets"), completed under social threat. Relative to individuals with normative social anxiety, individuals with elevated social anxiety had greater cognitive empathy and no differences in affective empathy, regardless of emotion type. As greater cognitive empathy can be maladaptive, Study 2 tested whether this could be down-regulated. Individuals with elevated social anxiety underwent emotional working memory training (eWMT) for negative emotional information, or control training (CT). Effects on an empathy measure completed under social threat were assessed. Cognitive empathy for negative emotions decreased following eWMT but not CT, and this was only evident for those with higher pre-training working memory capacity. Cognitive empathy for positive emotions and affective empathy were not affected. Overall, social anxiety is associated with aberrant elevated cognitive empathy for negative and positive emotions, and the deviation in cognitive empathy for negative emotions can be regulated with eWMT for certain individuals.Trial registration: Australian New Zealand Clinical Trials Registry identifier: ACTRN12618001196235..

Occupational class suicide risk: 12-year study of national coronial data.

BACKGROUND: Previous research showed that the Global Financial Crisis (GFC) was associated with a widening disparity in suicide rates between lower-class occupations and the highest-class occupations in Australia. There has been no research investigating whether this trend continued post-GFC. AIMS: This study aimed to investigate suicide rates by occupational class among employed Australians aged 15 years and over, between 2007 and 2018. METHOD: A population-level retrospective mortality study was conducted using data from the National Coronial Information System. Adjusted suicide rates were calculated over the period 2007 to 2018. Negative binomial regression models were used to assess the relationship between occupational class, gender and time, comparing post-GFC years (2010-2012, 2013-2015 and 2016-2018) with GFC years (2007-2009). RESULTS: Relative to the GFC period of 2007-2009, a significant reduction in suicide disparity between managers and other occupation groups was only observed among male labourers (rate ratios (RR) = 0.65, 95% CI 0.49-0.86) and male technicians/trades workers (RR = 0.73, 95% CI 0.56-0.96) for the period 2013-2015. CONCLUSION: Skilled manual and lower-skilled occupational classes remain at elevated risk of suicide in Australia. While a decreasing divergence in suicide rates was only observed between labourer and manager occupational classes post-GFC, this trend was not maintained over the later part of the study period (2016-2018). There is a need to further understand the relationship between contextual factors associated with suicide among the employed population, especially during periods of economic downturn.

A Spatial Analysis of Suicide Displacement at a High-Risk Cliff-Based Location Following Installation of a Means Restriction Initiative.

Means restriction interventions are recognised as highly effective for the deterrence of suicide attempts by jumping. While such interventions can lead to significant reductions in suicide, it is unclear whether these reductions represent a displacement effect, whereby individuals are instead choosing to attempt suicide at other nearby locations which offer the same means. The potential displacement of suicides as an unintended consequence of means restriction has been relatively unexplored to date. The only studies exploring displacement effects have focused on bridges, which are relatively easily contained sites; no studies have yet explored displacement effects at cliff-based high risk suicide locations (hotspots). Using Australian coronial data for the period of 2006-2019, we undertook joinpoint and kernel density analysis of suicides by jumping at a well-known cliff-based hotspot in Sydney, Australia, to determine whether there was evidence of displacement to local and broader surrounding cliffs following the installation of a multi-component harm minimization intervention (the Gap Park Masterplan). While slight decreases were noted in the immediate area subject to the structural intervention in the post-implementation period, alongside slight increases in the surrounding cliffs, there was no evidence for statistically significant changes. While kernel density analyses did not identify the emergence of any new hotspot locations in the post-implementation period, three existing hotspot sites of concern were found in our total area of interest, with greater than expected growth in the density of one of the hotspots. While we found no persuasive evidence of displacement, ongoing monitoring of the cliff-based location where the structural interventions were implemented is needed to ensure the ongoing safety of the area.

The effect of a therapeutic smartphone application on suicidal ideation in young adults: Findings from a randomized controlled trial in Australia.

BACKGROUND: Suicidal ideation is a major risk for a suicide attempt in younger people, such that reducing severity of ideation is an important target for suicide prevention. Smartphone applications present a new opportunity for managing ideation in young adults; however, confirmatory evidence for efficacy from randomized trials is lacking. The objective of this study was to assess whether a therapeutic smartphone application ("LifeBuoy") was superior to an attention-matched control application at reducing the severity of suicidal ideation. METHODS AND FINDINGS: In this 2-arm parallel, double-blind, randomized controlled trial, 455 young adults from Australia experiencing recent suicidal ideation and aged 18 to 25 years were randomly assigned in a 2:2 ratio to use a smartphone application for 6 weeks in May 2020, with the final follow-up in October 2020. The primary outcome was change in suicidal ideation symptom severity scores from baseline (T0) to postintervention (T1) and 3-month postintervention follow-up (T2), measured using the Suicidal Ideation Attributes Scale (SIDAS). Secondary outcomes were symptom changes in depression (Patient Health Questionnaire-9, PHQ-9), generalized anxiety (Generalized Anxiety Disorder-7, GAD-7), distress (Distress Questionnaire-5, DQ5), and well-being (Short Warwick-Edinburgh Mental Well-Being Scale, SWEMWBS). This trial was conducted online, using a targeted social media recruitment strategy. The intervention groups were provided with a self-guided smartphone application based on dialectical behavior therapy (DBT; "LifeBuoy") to improve emotion regulation and distress tolerance. The control group were provided a smartphone application that looked like LifeBuoy ("LifeBuoy-C"), but delivered general (nontherapeutic) information on a range of health and lifestyle topics. Among 228 participants randomized to LifeBuoy, 110 did not complete the final survey; among 227 participants randomized to the control condition, 91 did not complete the final survey. All randomized participants were included in the intent-to-treat analysis for the primary and secondary outcomes. There was a significant time × condition effect for suicidal ideation scores in favor of LifeBuoy at T1 (p < 0.001, d = 0.45) and T2 (p = 0.007, d = 0.34). There were no superior intervention effects for LifeBuoy on any secondary mental health outcomes from baseline to T1 or T2 [p-values: 0.069 to 0.896]. No serious adverse events (suicide attempts requiring medical care) were reported. The main limitations of the study are the lack of sample size calculations supporting the study to be powered to detect changes in secondary outcomes and a high attrition rate at T2, which may lead efficacy to be overestimated. CONCLUSIONS: LifeBuoy was associated with superior improvements in suicidal ideation severity, but not secondary mental health outcomes, compared to the control application, LifeBuoy-C. Digital therapeutics may need to be purposefully designed to target a specific health outcome to have efficacy. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12619001671156.

Consistency of trajectories of suicidal ideation and depression symptoms: Evidence from a randomized controlled trial.

BACKGROUND: Depression is a risk factor for suicidal ideation. However, suicidal ideation can occur in the absence of depression and treating depression may not reduce suicidal thinking. This study tested whether trajectories of suicidal thinking are concordant with trajectories of depressive symptoms and sought to identify factors associated with these trajectories. METHODS: Participants were community-based Australian adults (N = 418, 77% female) enrolled in a randomized controlled trial evaluating the effectiveness of an online cognitive-behavioral intervention for suicidal ideation. Separate linear growth mixture models were estimated across 12 months of follow-up to identify longitudinal trajectories of suicidal ideation and depression symptoms. Predictors of latent class membership were tested using logistic regression models. RESULTS: Two-class models were found to have optimal fit for both suicidal thinking and depressive symptoms. Trajectory classes of suicidal ideation were: (1) moderate severity decreasing over time; and (2) high severity remaining stable over time. Depression trajectories were: (1) moderate severity with a small decrease over time; and (2) high severity that decreased moderately over time. Lower perceived burdensomeness was associated with having a greater decrease in both suicidal thinking and depression. More severe mental health symptoms were associated with less decrease in depression symptoms but not with suicidal ideation trajectory. CONCLUSION: Class membership across the two outcomes and predictors of class membership were found to be largely independent. The lack of coupling in trajectories and predictors suggests that changes in suicidal thinking may occur independently of changes in depression.

Using Mobile Phone Sensor Technology for Mental Health Research: Integrated Analysis to Identify Hidden Challenges and Potential Solutions.

BACKGROUND: Mobile phone sensor technology has great potential in providing behavioral markers of mental health. However, this promise has not yet been brought to fruition. OBJECTIVE: The objective of our study was to examine challenges involved in developing an app to extract behavioral markers of mental health from passive sensor data. METHODS: Both technical challenges and acceptability of passive data collection for mental health research were assessed based on literature review and results obtained from a feasibility study. Socialise, a mobile phone app developed at the Black Dog Institute, was used to collect sensor data (Bluetooth, location, and battery status) and investigate views and experiences of a group of people with lived experience of mental health challenges (N=32). RESULTS: On average, sensor data were obtained for 55% (Android) and 45% (iOS) of scheduled scans. Battery life was reduced from 21.3 hours to 18.8 hours when scanning every 5 minutes with a reduction of 2.5 hours or 12%. Despite this relatively small reduction, most participants reported that the app had a noticeable effect on their battery life. In addition to battery life, the purpose of data collection, trust in the organization that collects data, and perceived impact on privacy were identified as main factors for acceptability. CONCLUSIONS: Based on the findings of the feasibility study and literature review, we recommend a commitment to open science and transparent reporting and stronger partnerships and communication with users. Sensing technology has the potential to greatly enhance the delivery and impact of mental health care. Realizing this requires all aspects of mobile phone sensor technology to be rigorously assessed.

Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer.

Importance: Application of deep learning algorithms to whole-slide pathology images can potentially improve diagnostic accuracy and efficiency. Objective: Assess the performance of automated deep learning algorithms at detecting metastases in hematoxylin and eosin-stained tissue sections of lymph nodes of women with breast cancer and compare it with pathologists' diagnoses in a diagnostic setting. Design, Setting, and Participants: Researcher challenge competition (CAMELYON16) to develop automated solutions for detecting lymph node metastases (November 2015-November 2016). A training data set of whole-slide images from 2 centers in the Netherlands with (n = 110) and without (n = 160) nodal metastases verified by immunohistochemical staining were provided to challenge participants to build algorithms. Algorithm performance was evaluated in an independent test set of 129 whole-slide images (49 with and 80 without metastases). The same test set of corresponding glass slides was also evaluated by a panel of 11 pathologists with time constraint (WTC) from the Netherlands to ascertain likelihood of nodal metastases for each slide in a flexible 2-hour session, simulating routine pathology workflow, and by 1 pathologist without time constraint (WOTC). Exposures: Deep learning algorithms submitted as part of a challenge competition or pathologist interpretation. Main Outcomes and Measures: The presence of specific metastatic foci and the absence vs presence of lymph node metastasis in a slide or image using receiver operating characteristic curve analysis. The 11 pathologists participating in the simulation exercise rated their diagnostic confidence as definitely normal, probably normal, equivocal, probably tumor, or definitely tumor. Results: The area under the receiver operating characteristic curve (AUC) for the algorithms ranged from 0.556 to 0.994. The top-performing algorithm achieved a lesion-level, true-positive fraction comparable with that of the pathologist WOTC (72.4% [95% CI, 64.3%-80.4%]) at a mean of 0.0125 false-positives per normal whole-slide image. For the whole-slide image classification task, the best algorithm (AUC, 0.994 [95% CI, 0.983-0.999]) performed significantly better than the pathologists WTC in a diagnostic simulation (mean AUC, 0.810 [range, 0.738-0.884]; P < .001). The top 5 algorithms had a mean AUC that was comparable with the pathologist interpreting the slides in the absence of time constraints (mean AUC, 0.960 [range, 0.923-0.994] for the top 5 algorithms vs 0.966 [95% CI, 0.927-0.998] for the pathologist WOTC). Conclusions and Relevance: In the setting of a challenge competition, some deep learning algorithms achieved better diagnostic performance than a panel of 11 pathologists participating in a simulation exercise designed to mimic routine pathology workflow; algorithm performance was comparable with an expert pathologist interpreting whole-slide images without time constraints. Whether this approach has clinical utility will require evaluation in a clinical setting.

A Review of Scales to Measure Social Anxiety Disorder in Clinical and Epidemiological Studies.

To advance research into social anxiety disorder (SAD) and provide efficacious treatments for individuals with SAD, researchers and clinicians must have effective assessment instruments for identifying the disorder in terms of its diagnostic criteria, symptoms, and the presence of specific maintaining factors. This review highlights the main lines of existing adult and youth research on scales that form part of diagnostic instruments that assess SAD, scales that measure social anxiety symptoms, and scales that measure theory-based psychological maintaining factors associated with SAD. The review also highlights methodological issues that impact on the use of the aforementioned scales. The continued refinement and comparative evaluation of measures for SAD, culminating in the ascertainment of optimal measures, will improve the assessment and identification of the disorder. Improved identification of the disorder will contribute to the advancement of SAD research and treatment.

Broad spectrum psychiatric comorbidity is associated with better executive functioning in an inpatient sample of individuals with schizophrenia.

BACKGROUND: Individuals with schizophrenia exhibit cognitive deficits but whether these deficits are exacerbated by broad spectrum psychiatric comorbidity (i.e., comorbidity that is inclusive of disorders from different diagnostic categories) is unclear. A broad spectrum approach to psychiatric comorbidity is an ecologically valid way to capture the diagnostic heterogeneity inherent in psychiatric presentations. OBJECTIVE: This study compared the attention, working memory, processing speed, and executive functioning of individuals with schizophrenia only relative to individuals with schizophrenia and broad spectrum psychiatric comorbidity. METHOD: Archival patient neuropsychological test data were obtained for a sample of patients with schizophrenia only (n=30) and a sample of patients with schizophrenia and psychiatric comorbidity (n=33). Relevant tests were used to form composite indices for the cognitive domains of attention, working memory, speed of processing, and executive functioning. RESULTS: Unexpectedly, individuals with schizophrenia and psychiatric comorbidity had significantly better executive functioning than individuals with schizophrenia only. There were no other significant differences. CONCLUSIONS: A broad spectrum approach to psychiatric comorbidity can help to account for differences in the executive functioning of individuals with schizophrenia. In clinical settings, individuals with schizophrenia and psychiatric comorbidity may benefit from intervention strategies that capitalize on their relatively higher executive functioning.

Can Emotional Working Memory Training Improve Cognitive Behavioral Therapy Outcomes for Social Anxiety Disorder: A Pilot Study.

Social anxiety disorder (SAD) models highlight maladaptive attention as a maintaining factor of SAD, potentially negatively impacting how individuals with SAD engage with cognitive behavioral therapy (CBT) content in a therapist's presence. Emotional working memory training (eWMT) has been shown to improve affective attentional control. This pilot study assessed the proposed methodology for a randomized controlled trial (RCT) to determine whether eWMT, by improving attentional control prior to internet-based CBT (iCBT), results in better CBT outcomes. The RCT would be considered feasible if the pilot study achieved rates ≥80% for eligible participants recruited, study measures completion, intervention completion, and participant retention. Results from 10 randomized participants showed rates ≥80% for recruitment of eligible participants and iCBT intervention completion. Completion of study measures, eWMT and Placebo training interventions, and participant retention were <80%. Results highlight the need to consider strategies to improve the methodology prior to the RCT.

Efficacy of BrighterSide, a Self-Guided App for Suicidal Ideation: Randomized Controlled Trial.

Background: Self-guided digital interventions can reduce the severity of suicidal ideation, although there remain relatively few rigorously evaluated smartphone apps targeting suicidality. Objective: This trial evaluated whether the BrighterSide smartphone app intervention was superior to a waitlist control group at reducing the severity of suicidal ideation. Methods: A total of 550 adults aged 18 to 65 years with recent suicidal ideation were recruited from the Australian community. In this randomized controlled trial, participants were randomly assigned to receive either the BrighterSide app or to a waitlist control group that received treatment as usual. The app was self-guided, and participants could use the app at their own pace for the duration of the study period. Self-report measures were collected at baseline, 6 weeks, and 12 weeks. The primary outcome was severity and frequency of suicidal ideation, and secondary outcomes included psychological distress and functioning and recovery. Additional data were collected on app engagement and participant feedback. Results: Suicidal ideation reduced over time for all participants, but there was no significant interaction between group and time. Similar improvements were observed for self-harm, functioning and recovery, days out of role, and coping. Psychological distress was significantly lower in the intervention group at the 6-week follow-up, but this was not maintained at 12 weeks. Conclusions: The BrighterSide app did not lead to a significant improvement in suicidal ideation relative to a waitlist control group. Possible reasons for this null finding are discussed.

Cognitive Maintaining Factors and Social Anxiety: The Mediating Role of Cognitive Fusion and Experiential Avoidance.

Cognitive fusion (CF) and experiential avoidance (EA) are two constructs of acceptance and commitment therapy that contribute to psychological distress. The current study aimed to examine whether CF and EA accounted for variance in the relationships between key cognitive maintaining factors of social anxiety and indicators of social anxiety. This issue was investigated using a longitudinal design in a nonclinical sample. Participants (N = 361) completed baseline measures of CF, EA, cognitive maintaining factors, and indicators of social anxiety, and the measures of indicators of social anxiety were recompleted 6 weeks later (N = 262). Results showed that baseline postevent processing had significant indirect effects on fear of negative evaluation at follow-up: (a) via CF, (b) via EA, and (c) via a serial pathway of CF → EA. Interventions that aim to reduce CF, in particular, may be a priority in reducing fear of negative evaluation associated with postevent processing.

The English Version of the Schema Inventory for Children: Psychometric Evaluation of a Measure of Early Maladaptive Schemas in a Primary School-Aged Sample.

Early maladaptive schemas (EMSs) are proposed to be maladaptive ways of thinking and feeling that develop from adverse experiences and basic needs not being met in childhood or adolescence. Once developed, EMSs increase vulnerability to psychopathology. Psychometric evaluations of EMS measures in children are scarce. This study aimed to evaluate the psychometric properties of the English version of the Schema Inventory for Children (SIC) in a community sample of youth aged 8 to 13 years. The SIC and measures of positive and negative automatic thoughts, social phobia symptoms, and depressed mood were administered to participants. Although a correlated 11-factor model was expected for the SIC, the optimal factor structure was a correlated six-factor model. EMS subscales corresponding to these six factors had acceptable internal consistency, and they had positive associations with the measures of negative automatic thoughts, social phobia symptoms, and depressive mood, as well as negative associations with the measure of positive automatic thoughts. These results indicate that EMSs in children may not be as differentiated as they are in adults. The results provide evidence for the reliability and validity of the English version of the SIC, justifying its use in contexts requiring the assessment of EMSs in children.

Risk of repeat self-harm and suicide death following an episode of hospital self-harm presentation among adolescents and young adults.

BACKGROUND: Self-harm is a critical issue affecting young people which could result in adverse outcomes including repeat episodes and suicide. In this study, we aimed to estimate the short-term and long-term risk of repeat self-harm and subsequent suicide death following self-harm presentations among adolescents and young adults. METHODS: Using linked data from the New South Wales (NSW) Emergency Department Data Collection (EDDC), the NSW Admitted Patient Data Collection (APDC), and cause of death unit record file (COD-URF), we collected all self-harm presentations to emergency departments and/or hospitals and suicide deaths between 2012 and 2019 in NSW, Australia. We used survival analysis models to estimate the incidence of repeat self-harm and suicide by time since the index self-harm and relative risks by sex, type of hospital presentation and count of self-harm records. RESULTS: In total, we identified 81,133 self-harm episodes among 48,547 individuals aged 10-29 years. Of 48,547 individuals who engaged in an index self-harm during the study period, 39.5 % (19,180) were aged between 15 and 19 years. The incidence of both repeat self-harm and suicide were highest in the year following the index self-harm presentation (repeat self-harm: 188.84 per 1000 person-years; suicide: 3.30 per 1000 person-years) and declined to 14.51 and 0.28 per 1000 person-years after five years. Among individuals indexed for self-harm at 15-29 years, males and those who were admitted to hospital for the index self-harm had the highest risk of both subsequent repeat self-harm and suicide death and those with 2 or more self-harm presentation records had the higher risk for subsequent suicide death. CONCLUSION: Adolescents and young adults with self-harm presentations were at a high risk of subsequent repeat self-harm and suicide death, especially the first year after presentations. Youth-specific early intervention and long-term management should be delivered accordingly, especially for those at early adolescence .

Understanding the Dimensions of Post-Event Processing: Applying a Bifactor Modeling Approach to the EPEPQ-15.

Social anxiety disorder is maintained in part by rumination about past social experiences, known as post-event processing. The Extended Post-Event Processing Questionnaire (EPEPQ-15) assesses post-event processing as three correlated factors. Competing against this structure is a bifactor model that has not yet been evaluated for the EPEPQ-15. These models were tested for the conventional state version of the EPEPQ-15 and a new trait version in two separate samples (Ns = 327 and 351). In both samples, the fit of the bifactor model was better than that of correlated factor models. Moreover, the results did not support the group factors, indicating that a unidimensional interpretation of the EPEPQ-15 is most appropriate. The general dimension of the EPEPQ-15 was highly correlated with social interaction anxiety, beliefs related to social anxiety, anticipatory processing, and safety behaviors. These results overall suggest post-event processing is best conceptualized as a unitary construct.

The Effectiveness of a Smartphone Intervention Targeting Suicidal Ideation in Young Adults: Randomized Controlled Trial Examining the Influence of Loneliness.

BACKGROUND: Loneliness is commonly reported by young people and has been shown to contribute to the rapid onset and escalation of depression and suicidal ideation during adolescence. Lonely people may also be particularly susceptible to disengaging from treatment early given the likelihood of their more complex clinical profiles leading to cognitive fatigue. While a smartphone intervention (LifeBuoy) has been shown to effectively reduce suicidal ideation in young adults, poor engagement is a well-documented issue for this therapeutic modality and has been shown to result in poorer treatment outcomes. OBJECTIVE: This study aims to determine whether loneliness affects how young people experiencing suicidal ideation engage with and benefit from a therapeutic smartphone intervention (LifeBuoy). METHODS: A total of 455 community-based Australian young adults (aged 18-25 years) experiencing recent suicidal ideation were randomized to use a dialectical behavioral therapy-based smartphone intervention (LifeBuoy) or an attention-matched control app (LifeBuoy-C) for 6 weeks. Participants completed measures of suicidal ideation, depression, anxiety, and loneliness at baseline (T0), post intervention (T1), and 3 months post intervention (T2). Piecewise linear mixed models were used to examine whether loneliness levels moderated the effect of LifeBuoy and LifeBuoy-C on suicidal ideation and depression across time (T0 to T1; T1 to T2). This statistical method was then used to examine whether app engagement (number of modules completed) influenced the relationship between baseline loneliness and suicidal ideation and depression across time. RESULTS: Loneliness was positively associated with higher levels of overall suicidal ideation (B=0.75, 95% CI 0.08-1.42; P=.03) and depression (B=0.88, 95% CI 0.45-1.32; P<.001), regardless of time point or allocated condition. However, loneliness did not affect suicidal ideation scores across time (time 1: B=1.10, 95% CI -0.25 to 2.46; P=.11; time 2: B=0.43, 95% CI -1.25 to 2.12; P=.61) and depression scores across time (time 1: B=0.00, 95% CI -0.67 to 0.66; P=.99; time 2: B=0.41, 95% CI -0.37 to 1.18; P=.30) in either condition. Similarly, engagement with the LifeBuoy app was not found to moderate the impact of loneliness on suicidal ideation (B=0.00, 95% CI -0.17 to 0.18; P=.98) or depression (B=-0.08, 95% CI -0.19 to 0.03; P=.14). CONCLUSIONS: Loneliness was not found to affect young adults' engagement with a smartphone intervention (LifeBuoy) nor any clinical benefits derived from the intervention. LifeBuoy, in its current form, can effectively engage and treat individuals regardless of how lonely they may be. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12619001671156; https://tinyurl.com/yvpvn5n8. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/23655.

Self-harm in 5-to-24 year olds: Retrospective examination of hospital presentations to emergency departments in New South Wales, Australia, 2012 to 2020.

There is some evidence that self-harm presentations in children and young people have increased over the past decade, yet there are few up-to-date studies examining these trends. This study aims to describe trends in the rates and severity of emergency department self-harm presentations for youth aged 5-24 years in New South Wales, Australia between 1 January 2012 and 31 December 2020. We analysed self-harm hospital presentations using join point analysis to compare quarterly growth in rates and urgency of presentation since 2012 by age group and sex. Binomial logistic modelling was used to identify risks for re-presentation for self-harm, including age group, sex, country of birth, mode of arrival, inpatient status, triage category, rurality, and socio-economic disadvantage. In total, 83,111 self-harm presentations for 51,181 persons were analysed. Overall rates of self-harm among those aged 5-24 years increased by 2.4% (p < .001) per quarter in females and 1.6% (p < .001) per quarter in males, with statistically significant average quarterly increases observed across all age groups. Overall and age-specific self-harm triage urgency rates increased statistically significantly for potentially serious, and potentially- and immediately life-threatening categories. A higher likelihood of re-presentation to any emergency department for self-harm was associated with younger age, female, residing in a regional area, arriving by ambulance, admitted as an in-patient, and a more severe index self-harm presentation. Hospital self-harm presentations have been growing steadily over the past decade, with the greatest growth in the youngest people. Understanding the reasons for these sustained upward trends is a priority for suicide prevention.

Concurrent and prospective associations between negative social-evaluative beliefs, safety behaviours, and symptoms during and following cognitive behavioural group therapy for social anxiety disorder.

BACKGROUND: Improving the delivery of cognitive-behavioural therapy (CBT) for social anxiety disorder (SAD) requires an in-depth understanding of which cognitive and behavioural mechanisms drive change in social anxiety symptoms (i.e., social interaction anxiety) during and after treatment. The current study explores the dynamic temporal associations between theory-driven cognitive and behavioural mechanisms of symptom change both during and following group CBT. METHODS: A randomized controlled trial of imagery-enhanced CBT (n = 51) versus traditional verbal CBT (n = 54) for social anxiety was completed in a community mental health clinic setting. This study included data collected from 12-weekly sessions and a 1-month follow-up session. Mixed models were used to assess magnitude of change over the course of treatment. Cross-lagged panel models were fit to the data to examine temporal relationships between mechanisms (social-evaluative beliefs, safety behaviours) and social interaction anxiety symptoms. RESULTS: Participants in both CBT groups experienced significant improvements across all cognitive, behavioural, and symptom measures, with no significant differences in the magnitude of changes between treatments. During treatment, greater social-evaluative beliefs (fear of negative evaluation, negative self-portrayals) at one time point (T) were predictive of more severe SAD symptoms and safety behaviours at T+1. Social-evaluative beliefs (fear of negative evaluation, probability and cost of social failure) and safety behaviours measured at post-treatment were positively associated with SAD symptoms at the 1-month follow-up. CONCLUSIONS: The current study identifies social-evaluative beliefs that may be important targets for symptom and avoidance reduction during and following CBT. Assessment of these social-evaluative beliefs throughout treatment may be useful for predicting future SAD symptoms and avoidance, and for adapting treatment to promote optimal change for patients.

Three-arm randomised controlled trial of an m-health app and digital engagement strategy for improving treatment adherence and reducing suicidal ideation in young people: study protocol.

INTRODUCTION: Youth suicidal ideation and behaviour is concerning due to its widespread prevalence, morbidity and potentially fatal consequences. Digital mental health interventions have been found to improve access to low-cost and high-quality support for a range of mental health issues, yet there are few digital interventions available for suicide prevention in young people. In addition, no studies have examined how digital engagement strategies may impact the engagement and efficacy of digital interventions in suicide prevention. The current protocol describes a three-arm parallel randomised controlled trial. A therapeutic smartphone application ('LifeBuoy'; intervention condition) will be tested against a condition that consists of the LifeBuoy application plus access to a digital engagement strategy ('LifeBuoy+engagement'; intervention condition) to determine whether the addition of the digital strategy improves app engagement metrics. To establish the efficacy of the LifeBuoy application, both of these intervention conditions will be tested against an attention-matched control condition (a placebo app). METHODS AND ANALYSIS: 669 young Australians aged 17-24 years who have experienced suicidal ideation in the past 30 days will be recruited by Facebook advertisement. The primary outcomes will be suicidal ideation severity and level of app engagement. Primary analyses will use an intention-to-treat approach and compare changes from baseline to 30-day, 60-day and 120-day follow-up time points relative to the control group using mixed-effect modelling. A subset of participants in the intervention groups will be interviewed on their experience with the app and engagement strategy. Qualitative data will be analysed using an inductive approach, independent of a theoretical confirmative method to identify the group themes. ETHICS AND DISSEMINATION: The study has been approved by the University of New South Wales Human Research Ethics Committee (HC210400). The results of the trial will be disseminated via peer-reviewed publications in scientific journals and conferences. TRIAL REGISTRATION NUMBER: ACTRN12621001247864.

Smartphone Sensor Data for Identifying and Monitoring Symptoms of Mood Disorders: A Longitudinal Observational Study.

BACKGROUND: Mood disorders are burdensome illnesses that often go undetected and untreated. Sensor technologies within smartphones may provide an opportunity for identifying the early changes in circadian rhythm and social support/connectedness that signify the onset of a depressive or manic episode. OBJECTIVE: Using smartphone sensor data, this study investigated the relationship between circadian rhythm, which was determined by GPS data, and symptoms of mental health among a clinical sample of adults diagnosed with major depressive disorder or bipolar disorder. METHODS: A total of 121 participants were recruited from a clinical setting to take part in a 10-week observational study. Self-report questionnaires for mental health outcomes, social support, social connectedness, and quality of life were assessed at 6 time points throughout the study period. Participants consented to passively sharing their smartphone GPS data for the duration of the study. Circadian rhythm (ie, regularity of location changes in a 24-hour rhythm) was extracted from GPS mobility patterns at baseline. RESULTS: Although we found no association between circadian rhythm and mental health functioning at baseline, there was a positive association between circadian rhythm and the size of participants' social support networks at baseline (r=0.22; P=.03; R2=0.049). In participants with bipolar disorder, circadian rhythm was associated with a change in anxiety from baseline; a higher circadian rhythm was associated with an increase in anxiety and a lower circadian rhythm was associated with a decrease in anxiety at time point 5. CONCLUSIONS: Circadian rhythm, which was extracted from smartphone GPS data, was associated with social support and predicted changes in anxiety in a clinical sample of adults with mood disorders. Larger studies are required for further validations. However, smartphone sensing may have the potential to monitor early symptoms of mood disorders.