Tag: News Approved

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The Comprehensive Assessment of Social Media Use: Development and Validation Study

Background: Nearly all youth use the internet daily, with many maintaining several social media accounts. As increasing numbers of young people engage online and the ways we communicate fundamentally change, it is increasingly important to ask: how do these shifts influence youth mental health? To better understand how social media may affect mental health, researchers require validated tools that capture young people’s heterogeneous experiences with social media. However, few available measures evaluate the full range of positive and negative behaviors associated with its use, limiting our ability to meaningfully advance interventions promoting online hygiene. Objective: This study aims to develop and validate the Comprehensive Assessment of Social Media Use (CASM). The CASM is a self-report survey measure that moves beyond simple duration or frequency of use and captures how young people engage with social media. Importantly, the CASM assesses both the positive and negative dimensions of social media engagement. Methods: Two studies are outlined in this paper. Study 1 outlines the process of item generation and exploratory factor analysis. Study 2 outlines confirmatory factor analysis and validity testing. Both studies were conducted online and enrolled a convenience sample of college-aged young adults. Study 1 enrolled 260 participants (mean age 19.73, SD 2.91; n=172, 66.2% female; n=164, 63.1% White; n=38, 14.6% lesbian, gay, bisexual, transgender/transsexual, and queer [LGBTQ]). Study 2 enrolled 508 participants (mean age 18.99, SD 1.17; n=323, 63.6% female; n=272, 53.5% White; n=58, 11.4% LGBTQ). Results: Exploratory and confirmatory factor analysis resulted in a 29-item CASM scale that assesses 7 distinct aspects of young adult social media use: self-branding, compulsive use, disruptive use, impulsive sharing, social engagement, induce negative emotions, and induce positive emotions. This model accounted for 61% of the variance in responses. The chi-squared test of model fit was significant (²=941, <.001; root mean square error of approximation=0.064; comparative fit index=0.855; Tucker-Lewis index=0.848; standardized root mean squared residual=0.060). Factor internal consistency reliability ranged from 0.699 to 0.817. Validity testing suggested moderate discriminant, convergent, and criterion validity. Conclusions: The CASM measures a broad range of social media behaviors, enabling researchers to more effectively examine associations between online engagement and mental health outcomes. We hope the CASM will help researchers better understand how young people interact with social media, and that this knowledge will inform the development of more targeted interventions promoting healthy online habits.
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Designing and Evaluating Digital Mental Health Interventions: Scoping Review

Background: The ongoing adoption and use of digital interventions offer promising opportunities to meet the growing demand for mental health support. The effectiveness, implementation, and usage of these interventions depend on how well they are designed and evaluated. However, given the emerging nature of design research in this area, there is still no clear consensus on the specific principles and guidelines for developing digital mental health interventions (DMHIs). There seems to be a lack of clarity regarding the best practices for designing and evaluating these tools. Objective: We aimed to investigate and report on the design principles and evaluation approaches used in digital interventions specific to mental health care. Additionally, we sought to outline how these principles and approaches are applied in research. Methods: This scoping review was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for scoping reviews. The literature search was performed in 2 electronic databases, SCOPUS and Web of Science, across 3 iterations from January 2024 to January 2025. A total of 2 independent reviewers screened and selected papers based on predefined inclusion and exclusion criteria, followed by data extraction from the selected studies. The data were then synthesized by categorizing the papers according to the primary research aim of each study. The inclusion criteria covered studies involving populations with mental health challenges or users of DMHIs, any digital tools for mental health care, and principles or strategies related to the design, evaluation, or implementation of DMHIs. Results: Our search identified 401 papers, of which 17 met the inclusion criteria for this review. Among these, 11 focused on evaluation studies, while 6 covered both design and evaluation studies (mixed). An iterative user-centered development process, expert inclusion, usability testing, specification of design elements, and user tracking and feedback were identified as common design principles used in studies focused on DMHIs. Evaluation approaches were shaped by the evaluation goal, which influenced the chosen methodologies. We also summarize the recommendations for implementation highlighted in some studies. Based on our findings, we propose 8 guidelines emphasizing stakeholder involvement in the development process and the need for clear justifications for design decisions, among other considerations. Conclusions: Design principles used in DMHI development include user-centered development, expert inclusion, and usability testing, while evaluation approaches often rely on randomized controlled trials to assess efficacy. Qualitative and mixed-method approaches are commonly adopted by studies to capture user experience and bridge both process and outcome measures. We recommend that future research explicitly report its design justification and adopt a multiperspective approach in the research and design of DMHIs.
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Errors in AI-Transformed Patient-Centered Mental Health Documentation Written by Psychiatrists: Qualitative Pre-Post Study

Background: Patients’ digital access to their personal health data is becoming increasingly common worldwide. However, medical documentation often contains technical language and sensitive information, which can lead to potential misunderstandings and distress among patients. These issues may be particularly impactful in mental health contexts. Large language models (LLMs) offer a promising approach by transforming clinician-generated health notes into language that is more patient-centered, nonmedicalized, and empathetic. However, risks related to accuracy and clinical safety have not been adequately investigated in psychiatry. Objective: This study aimed to qualitatively analyze the errors introduced by LLMs when transforming notes written by psychiatrists into patient-facing formats. It also highlights the implications for clinical communication and patient safety. Methods: Clinical notes (n=63) written by 19 psychiatrists in an outpatient treatment setting were collected, anonymized, and translated from German to English by humans. OpenAI GPT-3.5 Turbo was used to develop a preprompt that transformed these notes into a patient-centered, lay-readable form through an iterative process. Three psychiatrists qualitatively analyzed the LLM-revised documentation using Kuckartz content analysis. They compared the preconversion and postconversion notes to systematically identify and categorize LLM-induced errors. Results: Five categories of clinically relevant errors were identified: (1) clinical misinterpretations, particularly in critical assessments such as suicidality, where nuanced terminology was oversimplified or inaccurately represented; (2) attribution errors, where behaviors or roles within family dynamics or interactions were incorrectly attributed to different individuals; (3) content distortion errors, which were characterized by speculative additions, emotional exaggerations, and inappropriate contextual assumptions; (4) abbreviation and terminology errors, which resulted from inaccurate expansions of medical abbreviations and terms; and (5) structural and syntax errors, which resulted in ambiguity, particularly when the original notes were brief or bulleted. Despite significant improvements in the readability and overall linguistic fluency of the converted notes, these errors occurred. Conclusions: LLMs have the potential to transform psychiatric notes into patient-friendly formats. However, critical errors remain prevalent and can impair clinical judgment, understanding of patient circumstances, clarity of medication regimens, and interpretation of clinical observations. To safely integrate artificial intelligence–generated documentation into psychiatric care, clinician oversight and targeted model refinement are essential. Future research should explore strategies to mitigate these errors, assess their comprehensive clinical impact, and incorporate patient and provider perspectives to ensure robust implementation.
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<![CDATA[New US patent backs Denovo’s ANK3 biomarker guiding DB104 for treatment‑resistant depression, highlighting promising efficacy in selected patients.]]>
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<![CDATA[Lifestyle medicine pillars help reshape depression and anxiety treatment in psychiatry.]]>
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Serum cystatin C levels are independently correlated with cognitive impairment in individuals with cerebral small vessel disease

Background and purposePrevious studies have shown that serum cystatin C (CysC) is associated with cerebral small vessel disease (CSVD) and that elevated CysC levels are linked to an increased risk of cognitive impairment in the elderly. However, whether CysC is specifically associated with cognitive impairment in patients with CSVD remains unclear.MethodA total of 334 CSVD patients with available demographic, blood biomarker, and brain imaging data were included. Patients were divided into vascular cognitive impairment and normal cognition groups. Univariate analysis was used to compare baseline data, blood biomarkers, imaging features, and behavioral scores between the two groups. Binary logistic regression was used to evaluate the diagnostic value of cystatin C for CSVD-related cognitive impairment.ResultsCompared with the normal cognition group, the VCI group exhibited significantly elevated serum levels of CysC, homocysteine, urea nitrogen, creatinine, uric acid, fibrinogen, and D-dimer, along with a lower red blood cell count. The VCI group also showed a higher prevalence of severe periventricular white matter hyperintensity, severe deep white matter hyperintensity, severe total white matter hyperintensity, and brain atrophy. The combination of these eight blood biomarkers markedly improved the diagnostic performance for VCI (AUC = 0.672, 95% CI: 0.615–0.730, p < 0.001). Multivariate analysis revealed that elevated CysC levels (OR = 2.677, p = 0.041), age (OR = 1.067, p < 0.001), and severe total WMH (OR = 2.713, p < 0.001) were associated with CSVD-related cognitive impairment. After adjusting for confounding variables, serum CysC levels remained independently correlated with cognitive impairment (OR = 3.257, 95% CI: 1.192–8.899, p = 0.021).ConclusionSerum CysC levels are independently associated with cognitive impairment in CSVD patients.
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Effects of bifrontal-transcranial direct current stimulation combined with music listening on sleep quality, cortical activation and functional connectivity in patients with insomnia: a randomised controlled trial by fNIRS

BackgroundAlthough music listening and transcranial direct current stimulation (tDCS) alone have certain effects in the treatment of insomnia, the sleep regulatory effects and neural mechanisms of the combined treatment in patients with insomnia disorder (ID) are unclear. This study aimed to investigate the efficacy of combined bifrontal-tDCS (F3: anode, F4: cathode) with music listening in patients with ID using functional near-infrared spectroscopy (fNIRS).Methods76 ID patients were randomly divided into an intervention group (n=38) and a control group (n=38), and received 4 weeks of a total of 20 sessions of music + tDCS therapy and music + sham tDCS therapy (30-second stimulation with fade-in/fade-out to mimic somatic sensations), respectively. The Pittsburgh Sleep Quality Index Scale (PSQI), Self-rating Depression Scale (SDS), Self-rating Anxiety Scale (SAS), and Perceived Stress Scale (PSS-14) were compared between the two groups before and after treatment. Oxy-haemoglobin (HbO2) concentration and functional connectivity (FC) were assessed during the verbal fluency task using fNIRS.ResultsCompared with the control group, the PSQI total score (mean difference: -2.57 points, 95% CI: -4.43 to -0.71, p = 0.001), PSQI sub-scores except “sleep disturbance and daytime dysfunction”, SDS and SAS scores of the intervention group improved significantly after treatment. It was observed by fNIRS that the HbO2 concentration in the medial prefrontal cortex (mPFC), left dorsolateral prefrontal cortex (DLPFC), right ventrolateral prefrontal cortex, and right superior frontal cortex (SFC) increased significantly after treatment in the intervention group but was not superior to the control group. In addition, the FC enhancement of left SFC-left DLPFC and left SFC-mPFC after treatment was significantly better in the intervention group than in the control group, and the PSQI improvement was positively correlated with the FC enhancement of channel-averaged and left SFC-right DLPFC.ConclusionsCombining bifrontal-tDCS with music listening is more helpful in improving sleep quality and prefrontal functional connectivity in ID patients compared with music listening alone. For ID patients, music electrical stimulation headphones may be a safe, effective, and convenient new treatment strategy.Clinical trial registrationhttps://www.chictr.org.cn/, identifier ChiCTR2400086233.
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The long-term psychological processing of an autism spectrum disorder diagnosis in parents

IntroductionA child’s ASD diagnosis represents a critical event for parents, often requiring them to face the loss of their child’s ideal image and reevaluate the family life projects. The aim of this study is to explore how parents retrospectively reconstruct and integrate their child’s ASD diagnosis through autobiographical memories.Methods21 parents, 16 mothers and 5 fathers, that received the ASD diagnosis within five years, were administered the Reaction to Diagnosis Interview (RDI). Interviews were audio-recorded, transcribed verbatim and analyzed using a two levels approach. The first one to explore the patterns of meanings that emerged in the whole parents’ autobiographical memories through the Reflexive Thematic Analysis. The second one is to identify patterns of resolution or non-resolution of the impact of the diagnosis.ResultsFindings show suffering and struggling as main themes and subthemes and a prevalence of unresolved diagnoses; gender differences in the way of managing the child-related care tasks, efforts, and coping strategies emerged.DiscussionIn line with literature, our findings suggest that the availability of supportive resources plays a crucial role in facilitating parents’ adjustment and integration of the ASD experience and harmonizing gender differences. They also emphasize that the impact of ASD diagnosis is not a single event but an ongoing process of meaning-making which changes with the child’s developmental path. Our findings highlight the need for cognitive and emotional reconstruction and reframing of parents’ autobiographical memories. These processes play a kay role in shaping how the diagnosis experience is integrated into one’s narrative identity, creating opportunities for transforming the meaning of the remembered experience.
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Acupoint temperature as a biomarker: infrared thermography in the diagnosis of adolescents with major depressive disorder

BackgroundThe prevalence of adolescent major depressive disorder (MDD) is rising; however, diagnosis relies on subjective measures due to a lack of objective biomarkers. This study explored infrared thermography (IRT) as a non-invasive tool to quantify thermal radiation characteristics of acupoints in adolescents with MDD. The objective was to establish diagnostic models based on acupoint temperature-derived biomarkers.MethodsA prospective, multi-center observational study enrolled 108 participants (65 adolescents with MDD and 43 healthy controls [HCs]). We first examined correlations between acupoint temperatures and depression severity using Pearson analysis. Multiple linear and binary logistic regression models were developed to diagnose MDD and assess severity. The diagnostic model for MDD was visualized as a nomogram and validated using Receiver Operating Characteristic (ROC) curves, Hosmer-Lemeshow tests, calibration plots, and decision curve analysis (DCA). Internal validation was performed using the bootstrap method.ResultsAmong 27 acupoints analyzed, adolescents with MDD exhibited altered acupoint temperatures at Taiyang (EX-HN5), Quchi (LI11), Yanggu (SI5), and Waiqiu (GB36). Subsequent Pearson correlation analysis revealed negative correlations between the infrared relative temperatures of Taiyang (EX-HN5), Quchi (LI11), and Waiqiu (GB36) and depression severity (P = 0.001, r = -0.319; P = 0.022, r = -0.229; P = 0.001, r = -0.325) and a weak positive correlation between the infrared relative temperature of Yanggu (SI5) and depression severity (P = 0.043, r = 0.202). Building on these findings, two diagnostic models were developed: a linear regression model for depression severity of adolescents (Y = 52.25-9.52*TEX-HN5-13.07*TGB36) and a logistic regression model for adolescents with MDD diagnosis (P = ex/(1+ex), x = 0.22-1.14*TEX-HN5+0.45*TSI5-2.19*TGB36). The nomogram-based model demonstrated good calibration (Hosmer-Lemeshow P = 0.855), discrimination (AUC = 0.785, 95%CI: 0.693 – 0.876), and clinical utility. Internal validation using the bootstrap method produced a C-index of 0.752 (95% CI: 0.617 – 0.877), further confirming the model’s robustness.ConclusionsIn conclusion, acupoint temperature-based models show promising efficacy for the objective and non-invasive diagnosis and severity quantification of adolescents with MDD, offering valuable tools for early clinical intervention. Future studies should validate these findings across diverse populations and integrate multi-modal biomarkers to enhance diagnostic precision.Clinical Trial RegistrationClinicalTrials.gov, identifier NCT06750640.
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Stigma in adults with ADHD: a systematic review of types, experiences, and potential implications for quality of life

BackgroundAttention deficit hyperactivity disorder (ADHD) is a disorder characterized by hyperactive, impulsive, and/or inattentive symptoms. Adults with ADHD often report reduced quality of life (QoL) across social, educational, and occupational functioning. Part of these deficits may be attributed to stigma, which includes stereotypes, prejudices, discrimination, and negative labelling. While stigma’s effects on QoL have been extensively documented in other mental health conditions, the specific types and impacts of stigma experienced by adults with ADHD remain underexplored in recent reviews.AimsTo identify and describe the different types of stigmas experienced by adults with ADHD, while exploring how stigma may impact QoL’s key domains as defined by WHO (physical domain, psychological domain, level of independence, social relationships, environment, and spirituality/religion/personal beliefs).MethodsA literature search was conducted across APA PsycArticles, Embase, and Ovid MEDLINE(R) for ADHD AND stigma-related keywords. Eligible studies were English, peer-reviewed articles from the past decade involving adults (≥18) and describing or specifying at least one type of stigma.ResultsA total of 17 papers met the inclusion criteria. Stigma types included self-stigma and/or internalized stigma, perceived stigma, public stigma, and structural stigma. QoL domains affected included the psychological domain, social relationships, environment, and level of independence. Greater ADHD symptomatology was positively correlated with more internalized stigma, which in turn was linked to functional impairment, worse self-esteem, and poorer QoL. Self-stigma manifested as self-deprecating labels and ADHD devaluation. Perceived stigma hindered treatment seeking, medication compliance, and diagnostic disclosure, although associations with QoL were insignificant. Public stigma was the most investigated and related to negative societal attitudes, notably in academic contexts. Few studies looked at structural stigma; those that did identified structural barriers to care, though none directly assessed QoL outcomes.ConclusionStigma remains pervasive, though direct effects on QoL domains are less widely investigated. Future studies should investigate structural stigma in more depth and explore causal relationships between stigma and QoL.Systematic Review Registrationhttps://doi.org/10.17605/OSF.IO/Y52HK