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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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.

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
<![CDATA[Read our exclusive interview with Daniel R. Karlin, MD, MA, on the latest executive order, DT120 for the treatment of mental health disorders, and more.]]>

Oxygen extraction fraction is differentially associated with pathological biomarkers in Alzheimer’s disease and non-Alzheimer’s dementias

IntroductionWe aimed to understand the pathophysiological differences between 16 Alzheimer’s disease (AD) and 15 non-AD dementia patients by quantifying oxygen extraction fraction (OEF) in cortical (CGM) and deep gray matter (DGM) regions.MethodsTo achieve this, we used a novel MRI-based OEF mapping technique, QQ, which estimates OEF from routine multi-echo gradient echo data. Multiple linear regression analyses were performed to compare the associations between OEF and white matter hyperintensities (WMH) or cognitive impairment (measured by Montreal Cognitive Assessment (MoCA) between the two groups.ResultsIn the AD and non-AD group, OEF showed negative associations with WMH in DGM and positive associations with MoCA in DGM and CGM.DiscussionOur study suggests that QQ is a promising tool for differentiating between AD and non-AD dementias, by revealing abnormalities in tissue oxygen usage and their relationships to microvascular changes and cognitive impairment.

Quality, reliability, and transparency of late-life depression videos on Chinese social media: a cross-sectional study of Douyin, Rednotes, and BiliBili

BackgroundLate-life depression is common in older adults and is often under-recognized. Short-video platforms have become a major source of mental health information. However, content quality and transparency remain uncertain.MethodsWe conducted a cross-sectional assessment of highly viewed videos on late-life depression on three Chinese platforms. We searched each platform using the keyword in Chinese “Late-life depression”. We selected the top 200 videos by view count on Douyin, Rednotes (Xiaohongshu), and BiliBili. After exclusions, 562 videos were included (Douyin, n=188; Rednotes, n=188; BiliBili, n=186). Two medically trained raters scored videos using the Global Quality Score (GQS), modified DISCERN (mDISCERN), and JAMA benchmark criteria. We also coded content categories and creator types. We assessed platform differences using non-parametric tests. We examined associations between a limited engagement proxy, defined as the comment-to-view ratio, and quality scores using Spearman correlation.ResultsVideo duration differed across platforms (p<0.001). Engagement indicators were higher on Douyin and Rednotes than on BiliBili. Symptoms were the most common topic on all platforms. Prevention and intervention ranked second on Douyin and Rednotes. On BiliBili, causes and case-based analysis were also common. Overall quality was moderate. Mean GQS ranged from 2.96 to 3.05. Transparency was limited. Mean JAMA ranged from 1.91 to 2.04. Reliability was slightly higher on BiliBili based on mDISCERN. Creator type was strongly associated with scores. Expert and institutional videos scored higher than general and marketing-oriented accounts. Correlations between visible audience interaction and quality were weak.ConclusionHighly viewed late-life depression videos on major Chinese platforms show moderate quality and limited transparency. Exposure does not reliably signal higher-quality information. Platforms and health authorities should strengthen source disclosure and promote evidence-based content from qualified creators.

Scoping review of therapeutic approaches among individuals with secondary exercise addiction

Secondary exercise addiction shows high comorbidity with eating and body image disorders. Despite its substantial impact on physical and mental health and daily functioning, evidence on effective therapeutic interventions remains limited. The aim of this scoping review was to identify and describe therapeutic interventions applied to adult individuals with secondary exercise addiction. This review followed the PRISMA Sc-R guidelines and covered the years 2002–2024. Ultimately, five studies were included (four randomized controlled trials and one quasi-experimental study). Three studies applied psychotherapeutic interventions based on cognitive-behavioral models (Cognitive Behavioral Therapy, Lifestyle, Exercise, Attitudes, and Relationships Program, Physical Exercise and Dietary Therapy), while two integrated physical or nutritional components. A secondary analysis published in 2024 based on the LEAP trial dataset was identified but not treated as an independent study to avoid duplication. EBSCOhost, Web of Science, PubMed, and Google Scholar were searched from January to May 2025 using terms related to exercise addiction, exercise abuse, psychotherapy, intervention, and treatment. English-language studies were eligible if they described an intervention with at least one treated group with pre- and post-test measures; the participants of the study were adult patients suffering from eating disorders and exercise addiction (the therapy programs involved one inpatient and four outpatient treatments) and therapeutic intervention was carried out with outcomes based on exercise addiction level data. Four out of five included studies reported improvements in variables related to compulsivity, although these did not always imply a reduction in the amount of exercise, indicating that qualitative changes may be more relevant. Longer interventions showed more consistent effects, but even brief treatments generated positive changes in non-clinical populations. The examination of the research revealed a gap in studies addressing interventions for those with secondary exercise addiction, especially highlighting the need for randomized controlled trials (RCTs) with proper randomization methods.