Psychological Medicine最新文献

Background: Military Servicemembers and Veterans are at elevated risk for suicide, but rarely self-identify to their leaders or clinicians regarding their experience of suicidal thoughts. We developed an algorithm to identify posts containing suicide-related content on a military-specific social media platform.

Methods: Publicly-shared social media posts (n = 8449) from a military-specific social media platform were reviewed and labeled by our team for the presence/absence of suicidal thoughts and behaviors and used to train several machine learning models to identify such posts.

Results: The best performing model was a deep learning (RoBERTa) model that incorporated post text and metadata and detected the presence of suicidal posts with relatively high sensitivity (0.85), specificity (0.96), precision (0.64), F1 score (0.73), and an area under the precision-recall curve of 0.84. Compared to non-suicidal posts, suicidal posts were more likely to contain explicit mentions of suicide, descriptions of risk factors (e.g. depression, PTSD) and help-seeking, and first-person singular pronouns.

Conclusions: Our results demonstrate the feasibility and potential promise of using social media posts to identify at-risk Servicemembers and Veterans. Future work will use this approach to deliver targeted interventions to social media users at risk for suicide.

Background: Altered affective state recognition is assumed to be a root cause of aggressive behavior, a hallmark of psychopathologies such as psychopathy and antisocial personality disorder. However, the two most influential models make markedly different predictions regarding the underlying mechanism. According to the integrated emotion system theory (IES), aggression reflects impaired processing of social distress cues such as fearful faces. In contrast, the hostile attribution bias (HAB) model explains aggression with a bias to interpret ambiguous expressions as angry.

Methods: In a set of four experiments, we measured processing of fearful and angry facial expressions (compared to neutral and other expressions) in a sample of 65 male imprisoned violent offenders rated using the Hare Psychopathy Checklist-Revised (PCL-R, Hare, R. D. (1991). The psychopathy checklist-revised. Toronto, ON: Multi-Health Systems) and in 60 age-matched control participants.

Results: There was no evidence for a fear deficit in violent offenders or for an association of psychopathy or aggression with impaired processing of fearful faces. Similarly, there was no evidence for a perceptual bias for angry faces linked to psychopathy or aggression. However, using highly ambiguous stimuli and requiring explicit labeling of emotions, violent offenders showed a categorization bias for anger and this anger bias correlated with self-reported trait aggression (but not with psychopathy).

Conclusions: These results add to a growing literature casting doubt on the notion that fear processing is impaired in aggressive individuals and in psychopathy and provide support for the idea that aggression is related to a hostile attribution bias that emerges from later cognitive, post-perceptual processing stages.

This position paper by the international IMMERSE consortium reviews the evidence of a digital mental health solution based on Experience Sampling Methodology (ESM) for advancing person-centered mental health care and outlines a research agenda for implementing innovative digital mental health tools into routine clinical practice. ESM is a structured diary technique recording real-time self-report data about the current mental state using a mobile application. We will review how ESM may contribute to (1) service user engagement and empowerment, (2) self-management and recovery, (3) goal direction in clinical assessment and management of care, and (4) shared decision-making. However, despite the evidence demonstrating the value of ESM-based approaches in enhancing person-centered mental health care, it is hardly integrated into clinical practice. Therefore, we propose a global research agenda for implementing ESM in routine mental health care addressing six key challenges: (1) the motivation and ability of service users to adhere to the ESM monitoring, reporting and feedback, (2) the motivation and competence of clinicians in routine healthcare delivery settings to integrate ESM in the workflow, (3) the technical requirements and (4) governance requirements for integrating these data in the clinical workflow, (5) the financial and competence related resources related to IT-infrastructure and clinician time, and (6) implementation studies that build the evidence-base. While focused on ESM, the research agenda holds broader implications for implementing digital innovations in mental health. This paper calls for a shift in focus from developing new digital interventions to overcoming implementation barriers, essential for achieving a true transformation toward person-centered care in mental health.

Background: Adolescence is a critical period for brain development, consolidation of self-understanding, and onset of non-suicidal self-injury (NSSI). This study evaluated the RDoC (Research Domain Criteria) sub-construct of Self-Knowledge in relation to adolescent NSSI using multiple units of analysis.

Methods: One hundred and sixty-four adolescents assigned female at birth (AFAB), ages 12-16 years with and without a history of NSSI entered a study involving clinical assessment and magnetic resonance imaging (MRI), including structural, resting-state functional MRI (fMRI), and fMRI during a self-evaluation task. For imaging analyses, we used an a priori defined Self Network (anterior cingulate, orbitofrontal, and posterior cingulate cortices; precuneus). We first examined interrelationships among multi-level Self variables. We then evaluated the individual relationships between NSSI severity and multi-level Self variables (self-report, behavior, multi-modal brain Self Network measures), then conducted model testing and multiple regression to test how Self variables (together) predicted NSSI severity.

Results: Cross-correlations revealed key links between self-reported global self-worth and self-evaluation task behavior. Individually, greater NSSI severity correlated with lower global self-worth, more frequent and faster negative self-evaluations, lower anterior Self Network activation during self-evaluation, and lower anterior and posterior Self Network resting-state connectivity. Multiple regression analysis revealed the model including multi-level Self variables explained NSSI better than a covariate-only model; the strongest predictive variables included self-worth, self-evaluation task behavior, and resting-state connectivity.

Conclusions: Disruptions in Self-Knowledge across multiple levels of analysis relate to NSSI in adolescents. Findings suggest potential neurobiological treatment targets, potentially enhancing neuroplasticity in Self systems to facilitate greater flexibility (more frequently positive) of self-views in AFAB adolescents.

Background: The COVID-19 pandemic is associated with increases in child mental health problems, but the persistence of these changes in the post-pandemic era remains uncertain. Additionally, it is unclear whether changes in mental health problems during the pandemic exceed the anticipated increases as children age. This study controls for the linear effect of age in 1399 children, investigating the course of child-reported anxiety, depression, hyperactivity, and inattention symptoms during and after the pandemic, and identifies risk and protective factors that predict these mental health trajectories.

Methods: Children (51% male; ages 9-11 at the first timepoint) provided mental health ratings at three pandemic timepoints (July-August 2020; March-April 2021; November 2021-January 2022) and one post-pandemic timepoint (January-July 2023). Mothers reported pre-pandemic mental health (2017-2019) and socio-demographic factors. Children reported socio-demographic factors, risk (e.g. screen time, sleep), and resilience (e.g. optimism) factors during the first timepoint.

Results: Average mental health symptoms increased over time, with more children exceeding clinical cut-offs for poor mental health at each subsequent pandemic timepoint. Growth curve modeling, adjusting for age-related effects, revealed a curvilinear course of mental health symptoms across all domains. Examination of risk and protective factors revealed that pre-existing mental health symptoms and optimism were associated with the course of symptoms.

Conclusions: After considering age effects, children's mental health follows a curvilinear pattern over time, suggesting an initial decline followed by a rising trend in symptoms post-COVID. These findings underscore the continued need for additional resources and timely, evidence-based mental health prevention and intervention for children.

Background: Fear learning is a core component of conceptual models of how adverse experiences may influence psychopathology. Specifically, existing theories posit that childhood experiences involving childhood trauma are associated with altered fear learning processes, while experiences involving deprivation are not. Several studies have found altered fear acquisition in youth exposed to trauma, but not deprivation, although the specific patterns have varied across studies. The present study utilizes a longitudinal sample of children with variability in adversity experiences to examine associations among childhood trauma, fear learning, and psychopathology in youth.

Methods: The sample includes 170 youths aged 10-13 years (M = 11.56, s.d. = 0.47, 48.24% female). Children completed a fear conditioning task while skin conductance responses (SCR) were obtained, which included both acquisition and extinction. Childhood trauma and deprivation severity were measured using both parent and youth report. Symptoms of anxiety, externalizing problems, and post-traumatic stress disorder (PTSD) were assessed at baseline and again two-years later.

Results: Greater trauma-related experiences were associated with greater SCR to the threat cue (CS+) relative to the safety cue (CS-) in early fear acquisition, controlling for deprivation, age, and sex. Deprivation was unrelated to fear learning. Greater SCR to the threat cue during early acquisition was associated with increased PTSD symptoms over time controlling for baseline symptoms and mediated the relationship between trauma and prospective changes in PTSD symptoms.

Conclusions: Childhood trauma is associated with altered fear learning in youth, which may be one mechanism linking exposure to violence with the emergence of PTSD symptoms in adolescence.

Background: Patients can respond differently to intervention in the early phase of psychosis. Diverse symptomatic and functional outcomes can be distinguished and achieving one outcome may mean achieving another, but not necessarily the other way round, which is difficult to disentangle with cross-sectional data. The present study's goal was to evaluate implicative relationships between diverse functional outcomes to better understand their reciprocal dependencies in a cross-sectional design, by using statistical implication analysis (SIA).

Methods: Early psychosis patients of an early intervention program were evaluated for different outcomes (symptomatic response, functional recovery, and working/living independently) after 36 months of treatment. To determine which positive outcomes implied other positive outcomes, SIA was conducted by using the Iota statistical implication index, a newly developed approach allowing to measure asymmetrical bidirectional relationships between outcomes.

Results: Two hundred and nineteen recent onset patients with early psychosis were assessed. Results at the end of the three-years in TIPP showed that working independently statistically implied achieving all other outcomes. Symptomatic and functional recovery reciprocally implied one another. Living independently weakly implied symptomatic and functional recovery and did not imply independent working.

Conclusions: The concept of implication is an interesting way of evaluating dependencies between outcomes as it allows us to overcome the tendency to presume symmetrical relationships between them. We argue that a better understanding of reciprocal dependencies within psychopathology can provide an impetus to tailormade treatments and SIA is a useful tool to address this issue in cross-sectional designs.