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Behavioral Healthcare Treatment Access Patterns in Adolescents with Substance Use Disorders
No full textImportance: Despite 2 million adolescents (aged 12-17) in the United States having a substance use disorder (SUD), little is known regarding where they seek behavioral healthcare (e.g., mental health treatment, substance use treatment, or both). Adolescents have higher rates of co-occurring major depressive episodes (MDEs) than adults with SUDs, which may increase their use of mental health services. Understanding where adolescents with SUDs enter behavioral treatment is crucial to ensure adequate workforce preparedness to care for them where they seek help.
Objective: To determine where adolescents with SUDs, with or without co-occurring MDE, present to behavioral health treatment.
Design: This was a secondary data analysis of a cross-sectional nationally representative survey.
Setting: The National Survey on Drug Use and Health for adolescents (2022-2023). Data were analyzed between October 2025 and December 2025.
Participants: A sample of 24,541 adolescents between the ages of 12-17 from the United States of America.
Exposures: Treatment setting, SUD diagnosis, past year substance use, MDE diagnosis, adolescent age, biological sex, race and ethnicity, insurance status, household income, and study year.
Main Outcome(s) and Measure(s): Behavioral health treatment setting (i.e., mental health treatment, substance use treatment, both, or none) among adolescents with a SUD.
Results: Adolescents with a SUD were significantly more likely to engage in mental health (34.7% [95% CI: 30.9-38.8%]) than SU treatment (18.6% [95% CI: 15.8-21.8%], F1,50=62.2, p<.001). Similarly, adolescents with co-occurring SUD and MDE were significantly more likely to engage in mental health (70.7% [95% CI: 65.6-75.3%]) than SU treatment (21.2% [95% CI: 17.5-25.5%], F1,50=43.7, p<.001). Minoritized adolescents with a SUD (aPR = 0.82 [95% CI: 0.71-0.94], p = .007) were less likely, while female respondents with a SUD (aPR = 1.22 [95% CI: 1.07-1.40], p=.006) were more likely to receive any treatment.
Conclusions and Relevance: This study found that adolescents with a SUD were twice as likely, and adolescents with co-occurring SUD and MDE over three times more likely, to engage in mental health compared to substance use treatment. Clinically, these results suggest mental health treatment may serve as a critically important touchpoint to treat adolescents with SUDs
Reduced neural sensitivity to emotional faces and voices in preterm five-year-olds: A comparative study
No full textBackground: Accurate emotion processing is crucial for social development. Preterm birth is associated with neurodevelopmental alterations and increased vulnerability to subtle socio-emotional difficulties, often described within the preterm behavioral phenotype. Previous studies have reported impaired emotion recognition in preterm populations, but have largely relied on behavioral tasks and primarily focused on facial expressions. Because explicit emotion recognition is still developing in early childhood, objective neural markers of implicit emotion discrimination may be particularly informative for early detection.
Methods: We administered a series of frequency-tagging electroencephalography (EEG) paradigms to investigate neural sensitivity to brief changes in emotional expressions in a cohort of five-year-old preterm children (N = 66), and age-matched full-term peers (N = 32). Frequency-tagging EEG utilizes fast periodic stimulation to elicit synchronized brain responses measurable in the frequency domain. Neural sensitivity to changes in emotional expressions was examined in both the visual and auditory modality, using oddball paradigms with neutral faces or voices presented at base frequency and emotional expressions (either fearful or happy) presented as periodic oddballs. Linear mixed models were used to investigate the effects of group, emotion, and prematurity severity.
Results: All children showed implicit neural discrimination between neutral and emotional expressions. Compared to full-term peers, children born very preterm (≤32 weeks of gestation) showed reduced neural sensitivity to both facial and vocal emotion expression changes. Children born moderate-to-late preterm (33-36 weeks of gestation) also showed reduced neural sensitivity, but only for vocal expressions. Across modalities, reduced neural sensitivity to happy emotional expressions was associated with higher parent-reported social difficulties.
Conclusions: Five-year-old children born preterm show reduced neural sensitivity to brief changes in facial and vocal emotional expressions compared with full-term peers. Strikingly, the impact of prematurity severity differed between the visual and auditory modalities, indicating differential maturation of higher-level visual and auditory processing following preterm birth. These findings contribute to a more detailed understanding of socio-emotional development after preterm birth and highlight the importance of early, modality-sensitive monitoring of socio-emotional development across the entire preterm population
Perceptual psychology and climate action: three theoretical challenges
No full textTo what extent can basic research in perceptual psychology contribute to addressing the climate crisis? Accurate perception is necessary for knowing about climate change and for guiding a collective response. We identify three theoretical challenges for a climate-oriented perceptual psychology. (1) The knowledge problem: changes in the Earth’s climate are typically not directly perceivable, but are perceived via cognitive technologies such as scientific models, which introduce uncertainties. (2) The feedback problem: human action aimed at improving the Earth’s climate is necessary, but difficult to control, and potentially with unforeseeable side-effects. (3) The collective action problem: coordinating a response to climate breakdown is a collective challenge, demanding agreement on the epistemic basis of future action. These three challenges indicate the need for renewed theorizing about indirect knowledge and about action coordination and social decision-making under uncertainty. We end with some programmatic suggestions for future research
Purpose in life and blood-based biomarkers of brain health
No full textObjectives: Purpose in life is associated consistently with better cognitive outcomes. The association between purpose and neurobiomarkers of brain health has been less robust than the association with cognitive outcomes. This research uses the largest sample to date to test the association between purpose in life and four neurobiomarkers of brain health measured from plasma: The Aβ42/Aβ40 ratio, p-tau181, neurofilament light (NfL), and glial fibrillary acidic protein (GFAP). We further test whether higher purpose is associated with cognitive resilience against neuropathological burden (i.e., better cognitive performance relative to the amount of neuropathology).
Methods: Data were from the Health and Retirement Study. Participants (N=4193; Mage=68.87, SD=10.17) reported on their purpose in life and provided venous blood. Biomarkers were assessed using Quanterix’s Simoa platforms. Linear regression tested the association between purpose and the four neurobiomarkers. Residual and interaction-based approaches evaluated cognitive resilience.
Results: Purpose in life was associated with lower NfL accounting for sociodemographic factors (β=-.06, p<.001). Clinical and behavioral covariates accounted for half of this association, but it persisted (β=-.03, p=.007). Purpose was unrelated to the other three neurobiomarkers. Purpose in life was associated with greater cognitive resilience when tested with the residual approach (β=.11, p<.001) but not the interaction approach (βinteraction=.01, p=.372).
Discussion: In the largest sample to date, individuals with more purpose in life had less neuronal injury, as measured with NfL. Purpose was unrelated to other common neurobiomarkers of brain health
Effects of biofeedback on musicians' mental health and performance: a systematic review
No full textBackground. Music performance anxiety is a common and debilitating problem among musicians. Biofeedback interventions have been increasingly investigated as non-pharmacological approaches to reduce anxiety and enhance musical performance; however, evidence regarding their effectiveness, training characteristics, and outcome specificity remains fragmented. Aim. This systematic review aimed to synthesize evidence on the effects of biofeedback techniques on musician's mental health and performance. Methods. A systematic literature search was conducted across Scopus, PsycINFO, and PubMed. Studies investigating biofeedback interventions targeting anxiety, performance, or physiological outcomes in musicians were included. Study selection followed PRISMA 2020 guidelines. Results. Eleven studies met the inclusion criteria. Interventions included electroencephalography (EEG) - based neurofeedback, autonomic biofeedback, and multimodal biofeedback approaches, with durations ranging from single-session protocols to multi-week and multi-month training programs. Anxiety-related outcomes were most consistently improved by autonomic and multimodal biofeedback, whereas EEG neurofeedback more frequently yielded improvements in expert-rated musical performance. Physiological modulation, including changes in EEG activity, reductions in muscle tension, and improvements in heart rate variability, was observed across intervention types. Conclusions. Biofeedback interventions represent a promising non-pharmacological approach for reducing performance anxiety in musicians. Future studies should standardize outcome measures, define optimal intervention dosage, and directly compare different biofeedback modalities to inform evidence-based implementation in musical performance contexts
University Students' Situational Motivation over a Statistics Course and Relations to Anxiety
No full textWe examined the intra- and interindividual variability of students’ motivation (i.e., expectancies, values, and costs) and statistics anxiety, how motivation relates to anxiety within situations, and whether there are differences in these relations between students. We applied an intensive longitudinal design and multilevel structural equation modelling approach in a sample of 154 Finnish university students enrolled in a statistics course. The results showed that anxiety was negatively predicted by expectancies and values, and positively by costs, but that there were significant individual differences in these associations. For example, some students experienced higher anxiety when they had low expectancies, whilst some when they had high expectancies. Furthermore, the results showed that expectancies and values negatively predicted relatively higher anxiety for a particular student. Overall, the findings highlight the particular role of expectancies, values, and costs on statistics anxiety and the variability between individuals across learning situations
Social connection features predicting loneliness: A longitudinal, interpretable machine-learning analysis
No full textBackground: Loneliness is increasingly recognized as a major global health concern. As a marker of poor social health, loneliness may emerge when certain aspects of social connection are missing. Yet, it remains unclear to what extent and which features of social connection contribute to a vulnerability of loneliness. In this study, we examined how 24 features of individuals’ social connections spanning structural, functional and quality dimensions predict loneliness both at the same time point and over a two-year follow-up.
Methods: Using fine-grained, tie-specific data from a population-based Dutch cohort aged 18–93 years at baseline (N = 6,852) and at follow-up (N = 3,175), we evaluated which social connection features are predictive of loneliness using random-forest models at both timepoints and across age groups.
Findings: Across both analyses, network quality was the strongest predictor of loneliness. Good-quality and strained relationships, friends-know-family, and network size consistently predicted loneliness. Being in a steady relationship was a top predictor at baseline but less important at follow-up. Functional aspects were generally less predictive. Models explained 24% of baseline and 44% of follow-up variance.
Interpretation: These findings suggest that loneliness is most strongly linked to the quality of one’s social ties rather than their function, and that individuals embedded in low-quality or strained networks are particularly vulnerable. The results also underscore that loneliness is shaped by a broader constellation of factors beyond social connections
b4Math: a digital assessment tool for early symbolic numerical skills in kindergarten
No full textEarly symbolic numerical skills constitute a foundational component of later mathematical learning, yet rigorously validated assessment tools for preschool-aged children remain scarce in Latin American contexts. The present study aimed to develop and psychometrically validate b4Math, a digital screening tool designed to assess early symbolic numerical skills in children attending the final year of preschool (age 5). b4Math evaluates five domain-specific numerical processes: cardinality, counting sequence, number identification, symbolic number comparison, and ordinality, aligned with curricular objectives for early mathematics education. Data were drawn from two cohorts in Chile (total N = 357), collected across two waves (2023–2024). Construct validity was examined using confirmatory factor analysis (CFA). Four dichotomous-response tasks (cardinality, identification, comparison, and ordinality) were modeled using a correlated four-factor CFA with the WLSMV estimator, showing excellent fit and clear multidimensional structure. The counting-sequence task, yielding continuous responses, was analyzed separately using a single-factor CFA with robust maximum likelihood estimation (MLR), demonstrating high factor loadings and internal consistency. Measurement invariance across gender and temporal stability (test–retest) were supported. Internal consistency indices were satisfactory across subscales. External validity was established through associations between b4Math factor scores and mathematical achievement as measured by the Applied Problems subtest of the Woodcock–Muñoz Battery. Overall, results support the reliability and validity of b4Math as a culturally pertinent, digitally delivered assessment of early symbolic numerical skills. b4Math offers educators and researchers in Latin America an efficient tool for screening and monitoring foundational numerical competencies critical for later mathematics learning
The Bereaved Voices Project: A protocol for community-based psychological autopsy research to understand and prevent suicide in autistic people
No full textBackground
Since 2011, there has been a threefold increase in suicide deaths amongst autistic mental health patients in the UK. Autistic people report negative experiences of help-seeking for suicidal thoughts and behaviours, which increase hopelessness and suicidal intent. Suicide theories originating in non-autistic people are less accurate in explaining suicidal thoughts and behaviours in autistic people, but such theories have not yet been applied to explore suicide deaths in autistic adults.
Methods
This community-based psychological autopsy study harnesses a novel multi-disciplinary team of bereaved people, autism and suicide experts and practising psychiatrists to identify: (i) risk and protective factors for death by suicide and/or self-inflicted injury amongst autistic people; (ii) service-level improvements to avoid future deaths; and (iii) the feasibility and acceptability of research methods to inform future research in this area. Mixed-methods quantitative and qualitative analyses will inform the development of: (i) a conceptual model of pathways to suicide in autistic people; (ii) future service pathways and models; and (iii) methods guidance for the conduct of safe future research on this topic.
Discussion
Given scant previous research in this area, this project is the first to take a systematic approach to understand the experiences of autistic people who lost their lives to suicide from the perspective of those closest to them in life. Study outcomes will lead to: (i) increased conceptual understanding to inform future research and clinical practice; (ii) specific proposals for service level improvements, such as adaptations to processes such as mental health admission, removal of liberty, individual risk formulation and support; and (iii) the safe inclusion of bereaved autistic people in future research. Taken together, this novel study will significantly advance our understanding of suicide in autistic people to inform targeted prevention strategies and clinical improvements to practice
Body Dysmorphic Disorder in the Digital Age: Algorithmic Mechanisms and Clinical Implications for Adolescents
No full textBackground: Body dysmorphic disorder (BDD) affects approximately 1.8% of adolescent females and 0.3% of males, with onset typically between ages 12 and 16 years. Image-based social media platforms and algorithmic content curation have created digital environments that may influence appearance-related psychopathology in vulnerable youth, yet no synthesis has examined these mechanisms with attention to Child and Adolescent Mental Health Services (CAMHS) practice.
Methods: This narrative review synthesised evidence on associations between social media use and BDD symptoms in adolescents through searches of PubMed, Scopus, and Google Scholar (January 2015 to December 2025), focusing on algorithmic mechanisms, emerging digital phenomena, gender-specific presentations, and clinical implications.
Results: Cross-sectional evidence demonstrates platform-specific effects, with image-based platforms showing significant associations with BDD symptoms. Appearance-motivated social media use is more predictive than total screen time, and intolerance of uncertainty may moderate this relationship. Algorithmic personalisation may create filter bubbles increasing appearance-focused content exposure, while variable-ratio reinforcement maintains compulsive engagement. Gender differences are evident: females predominantly experience skin and weight concerns amplified by filtered imagery, while males increasingly present with muscularity preoccupations linked to "looksmaxxing" communities. Emerging phenomena include Zoom dysmorphia and AI-powered appearance tools.
Conclusions: This review proposes the Algorithmic Amplification Model of Digital BDD and introduces the Digital BDD Screening Tool for Adolescents (DBST-A) for CAMHS assessment. Cognitive-behavioural therapy requires adaptation incorporating digital exposure hierarchies and algorithmic literacy psychoeducation. Clinicians should routinely enquire about platform-specific behaviours, editing practices, and engagement with AI tools and appearance communities
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