Social and occupational outcomes for young people who attend early intervention mental health services: a longitudinal study.

OBJECTIVE: To identify trajectories of social and occupational functioning in young people during the two years after presenting for early intervention mental health care; to identify demographic and clinical factors that influence these trajectories. DESIGN: Longitudinal, observational study of young people presenting for mental health care. SETTING: Two primary care-based early intervention mental health services at the Brain and Mind Centre (University of Sydney), 1 June 2008 - 31 July 2018. PARTICIPANTS: 1510 people aged 12-25 years who had presented with anxiety, mood, or psychotic disorders, for whom two years' follow-up data were available for analysis. MAIN OUTCOME MEASURES: Latent class trajectories of social and occupational functioning based on growth mixture modelling of Social and Occupational Assessment Scale (SOFAS) scores. RESULTS: We identified four trajectories of functioning during the first two years of care: deteriorating and volatile (733 participants, 49%); persistent impairment (237, 16%); stable good functioning (291, 19%); and improving, but late recurrence (249, 16%). The less favourable trajectories (deteriorating and volatile; persistent impairment) were associated with physical comorbidity, not being in education, employment, or training, having substance-related disorders, having been hospitalised, and having a childhood onset mental disorder, psychosis-like experiences, or a history of self-harm or suicidality. CONCLUSIONS: Two in three young people with emerging mental disorders did not experience meaningful improvement in social and occupational functioning during two years of early intervention care. Most functional trajectories were also quite volatile, indicating the need for dynamic service models that emphasise multidisciplinary interventions and measurement-based care.

eHealth Tools That Assess and Track Health and Well-being in Children and Young People: Systematic Review.

BACKGROUND: eHealth tools that assess and track health outcomes in children or young people are an emerging type of technology that has the potential to reform health service delivery and facilitate integrated, interdisciplinary care. OBJECTIVE: The aim of this review is to summarize eHealth tools that have assessed and tracked health in children or young people to provide greater clarity around the populations and settings in which they have been used, characteristics of digital devices (eg, health domains, respondents, presence of tracking, and connection to care), primary outcomes, and risks and challenges of implementation. METHODS: A search was conducted in PsycINFO, PubMed or MEDLINE, and Embase in April 2020. Studies were included if they evaluated a digital device whose primary purpose was to assess and track health, focused on children or young people (birth to the age of 24 years), reported original research, and were published in peer-reviewed journals in English. RESULTS: A total of 39 papers were included in this review. The sample sizes ranged from 7 to 149,329 participants (median 163, mean 5155). More studies were conducted in urban (18/39, 46%) regions than in rural (3/39, 8%) regions or a combination of urban and rural areas (8/39, 21%). Devices were implemented in three main settings: outpatient health clinics (12/39, 31%), hospitals (14/39, 36%), community outreach (10/39, 26%), or a combination of these settings (3/39, 8%). Mental and general health were the most common health domains assessed, with a single study assessing multiple health domains. Just under half of the devices tracked children's health over time (16/39, 41%), and two-thirds (25/39, 64%) connected children or young people to clinical care. It was more common for information to be collected from a single informant (ie, the child or young person, trained health worker, clinician, and parent or caregiver) than from multiple informants. The health of children or young people was assessed as a primary or secondary outcome in 36% (14/39) of studies; however, only 3% (1/39) of studies assessed whether using the digital tool improved the health of users. Most papers reported early phase research (formative or process evaluations), with fewer outcome evaluations and only 3 randomized controlled trials. Identified challenges or risks were related to accessibility, clinical utility and safety, uptake, data quality, user interface or design aspects of the device, language proficiency or literacy, sociocultural barriers, and privacy or confidentiality concerns; ways to address these barriers were not thoroughly explored. CONCLUSIONS: eHealth tools that assess and track health in children or young people have the potential to enhance health service delivery; however, a strong evidence base validating the clinical utility, efficacy, and safety of tools is lacking, and more thorough investigation is needed to address the risks and challenges of using these emerging technologies in clinical care. At present, there is greater potential for the tools to facilitate multi-informant, multidomain assessments and longitudinally track health over time and room for further implementation in rural or remote regions and community settings around the world.

Friendship in War: Camaraderie and Prevention of Posttraumatic Stress Disorder Prevention.

Aspects of social support during combat deployment, such as unit cohesion, have been shown to affect later posttraumatic stress disorder (PTSD) development among veterans. We utilized a longitudinal database to assess how relationship quality with fellow soldiers in World War II (WWII) might be linked with postwar PTSD symptoms. Data were available on 101 men who experienced combat exposure in WWII, documented through postwar assessment. Upon study entry (1939 to 1942), data were collected on the quality of participants' early childhood relationships and their emotional adjustment during college. Data on WWII experiences were collected in 1946. Relationship quality with fellow soldiers in WWII was examined as a moderator of the link between combat exposure and postwar PTSD symptoms. Prewar emotional adjustment was examined as a mediator between quality of childhood relationships and subsequent quality of relationships quality with fellow soldiers during war. Better quality relationships with fellow soldiers attenuated (i.e., moderated) the link between combat exposure severity and PTSD symptom count, explaining a significant percent of the variance, R2 = .19, p < .001. There was also a significant indirect mediation effect of childhood relationship quality on relationships with soldiers through prewar emotional adjustment, ab = 0.02, 95% BCa CI [0.01, 0.05]. Results suggest that better peer relationship quality during deployment may reduce the likelihood of subsequent PTSD symptom development, and that the quality of early relationships may set the stage for better relationships during stressful contexts such as war. These findings have implications for PTSD risk factor screening prior to deployment, and underscore the importance of interpersonal support among soldiers during deployment.

Out of fright, out of mind: impaired memory for information negated during looming threat.

People often need to update representations of information upon discovering them to be incorrect, a process that can be interrupted by competing cognitive demands. Because anxiety and stress can impair cognitive performance, we tested whether looming threat can similarly interfere with the process of updating representations of a statement's truthfulness. On each trial, participants saw a face paired with a personality descriptor. Each pairing was followed by a signal indicating whether the pairing was "true", or "false" (a negation of the truth of the statement), and this signal could be followed by a warning of imminent electric shock (i.e., the looming threat). As predicted, threat of shock left memory for "true" pairings intact, while impairing people's ability to label negated pairings as untrue. Contrary to our predictions, the pattern of errors for pairings that were negated under threat suggested that these mistakes were at least partly attributable to participants forgetting that they saw the negated information at all (rather than being driven by miscategorization of the pairings as true). Consistent with this, linear ballistic accumulator modelling suggested that this impaired recognition stemmed from weaker memory traces rather than decisional processes. We suggest that arousal due to looming threat may interfere with executive processes important for resolving competition between mutually suppressive tags of whether representations in memory are "true" or "false".

Right Care, First Time: Developing a Theory-Based Automated Protocol to Help Clinically Stage Young People Based on Severity and Persistence of Mental Illness.

Most mental disorders emerge before the age of 25 years and, if left untreated, have the potential to lead to considerable lifetime burden of disease. Many services struggle to manage high demand and have difficulty matching individuals to timely interventions due to the heterogeneity of disorders. The technological implementation of clinical staging for youth mental health may assist the early detection and treatment of mental disorders. We describe the development of a theory-based automated protocol to facilitate the initial clinical staging process, its intended use, and strategies for protocol validation and refinement. The automated clinical staging protocol leverages the clinical validation and evidence base of the staging model to improve its standardization, scalability, and utility by deploying it using Health Information Technologies (HIT). Its use has the potential to enhance clinical decision-making and transform existing care pathways, but further validation and evaluation of the tool in real-world settings is needed.

Predicting self-harm within six months after initial presentation to youth mental health services: A machine learning study.

BACKGROUND: A priority for health services is to reduce self-harm in young people. Predicting self-harm is challenging due to their rarity and complexity, however this does not preclude the utility of prediction models to improve decision-making regarding a service response in terms of more detailed assessments and/or intervention. The aim of this study was to predict self-harm within six-months after initial presentation. METHOD: The study included 1962 young people (12-30 years) presenting to youth mental health services in Australia. Six machine learning algorithms were trained and tested with ten repeats of ten-fold cross-validation. The net benefit of these models were evaluated using decision curve analysis. RESULTS: Out of 1962 young people, 320 (16%) engaged in self-harm in the six months after first assessment and 1642 (84%) did not. The top 25% of young people as ranked by mean predicted probability accounted for 51.6% - 56.2% of all who engaged in self-harm. By the top 50%, this increased to 82.1%-84.4%. Models demonstrated fair overall prediction (AUROCs; 0.744-0.755) and calibration which indicates that predicted probabilities were close to the true probabilities (brier scores; 0.185-0.196). The net benefit of these models were positive and superior to the 'treat everyone' strategy. The strongest predictors were (in ranked order); a history of self-harm, age, social and occupational functioning, sex, bipolar disorder, psychosis-like experiences, treatment with antipsychotics, and a history of suicide ideation. CONCLUSION: Prediction models for self-harm may have utility to identify a large sub population who would benefit from further assessment and targeted (low intensity) interventions. Such models could enhance health service approaches to identify and reduce self-harm, a considerable source of distress, morbidity, ongoing health care utilisation and mortality.

Oculomotor capture is influenced by expected reward value but (maybe) not predictiveness.

A large body of research has shown that learning about relationships between neutral stimuli and events of significance - rewards or punishments - influences the extent to which people attend to those stimuli in the future. However, different accounts of this influence differ in terms of the critical variable that is proposed to determine learned changes in attention. We describe two experiments using eye-tracking with a rewarded visual search procedure to investigate whether attentional capture is influenced by the predictiveness of stimuli (i.e., the extent to which they provide information about upcoming events) or by their absolute associative value (i.e., the expected incentive value of the outcome that a stimulus predicts). Results demonstrated a clear influence of associative value on the likelihood that stimuli will capture eye-movements, but the evidence for a distinct influence of predictiveness was less compelling. The results of these experiments can be reconciled within a simple account under which attentional prioritization is a monotonic function of the expected, subjective value of the reward that is signalled by a stimulus.