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PubMed2026

Feasibility and acceptability of skills training in affective recovery (STAR) video and TextSTAR text message program for recent sexual assault survivors.

Background: Sexual assault (SA) affects more than 50% of women in the United States and is associated with elevated risk for impairing posttraumatic stress symptoms and substance, particularly opioid, misuse. Intervening following SA exposure could attenuate these risks.Objective: This study examined the acceptability and feasibility of a 17-minute video, Skills Training in Affective Recovery (STAR) and a 21-day text message program (TextSTAR), that were delivered in the acute post-SA period to prevent the onset or escalation of posttraumatic stress symptoms and substance misuse. The interventions provide psychoeducation about trauma, strategies to reduce fear and avoidance, suggestions to increase social support, and coping strategies for substance use.Method: Participants were 50 women age 18 or older who presented for a Sexual Assault Medical Forensic Exam (SAMFE) within seven days of a SA. Using a Sequential Multiple Assignment Randomized Controlled Trial (SMART) design, participants were randomized to receive the STAR video (n = 25) or no video (n = 25) at the SAMFE. Those who received the video answered questions about video acceptability immediately after viewing the video. At 1-week post-SAMFE, participants completed online questionnaires about substance use and posttraumatic stress; those above threshold on acute stress or opioid use (n = 36) were randomized to TextSTAR (n = 18) or no-text program (n = 18). Participants completed weekly online surveys 2-4 weeks post-SAMFE about symptoms and text program acceptability.Results: Participants found STAR and TextSTAR at least moderately acceptable; 80% who received STAR found it extremely acceptable while 60-90% (depending on timepoint) who received TextSTAR found it at least moderately acceptable. Our ability to enroll 50 participants and retain 94% at 1 week and 90% at 4 weeks suggests the intervention trial is feasible.Conclusions: STAR and TextSTAR are acceptable and feasible brief interventions for recent sexual assault survivors.Trial registration: ClinicalTrials.gov identifier: NCT06456190.

Humans↗

PubMed2026

Effect of Global Postural Re-Education in Individuals With Text Neck Syndrome: A Randomized Controlled Trial.

BACKGROUND AND PURPOSE: This study investigated the effect of Global Postural Re-Education (GPR) versus conventional physical therapy in text neck syndrome (TNS). A prospective, single-blinded, parallel-group randomized controlled trial design was used. METHODS: Sixty participants with TNS (aged 18-40 years) were randomly assigned to either conventional treatment or GPR plus conventional treatment. Both groups received supervised therapy for three sessions per week over 4 weeks. Outcome measures included craniovertebral and shoulder angles assessed by photogrammetry, pain intensity via Visual Analog Scale, and Cervical Range of Motion via a smartphone application (Clinometer). Measured before and after the intervention. RESULTS: Within-group analyses showed significant improvements in pain and CROM in both groups (p < 0.001). However, the between-group analysis revealed no superiority of GPR for pain or CROM (p > 0.05). In contrast, GPR demonstrated statistically significant superiority in postural correction, with greater improvements in craniovertebral angle (MD: 2.14°; 95% CI: 0.69-3.59; p = 0.005) and shoulder angle (MD: 3.2°; 95% CI: 0.33-6.07; p = 0.03), exceeding MCID thresholds and indicating clinically meaningful benefits. However, these findings should be interpreted with caution because of the longer session duration in the GPR group. DISCUSSION: Incorporating Global Postural Reeducation (GPR) into conventional treatment provided significant additional benefits for postural parameters (craniovertebral and shoulder angles) in individuals with text neck syndrome. However, GPR demonstrated no added superiority over conventional treatment alone regarding pain intensity and cervical range of motion outcomes.

Humans↗

PubMed2026

Behaviourally informed text message reminders to increase cervical screening attendance in people with severe mental illness: the OPTIMISE pilot randomised controlled trial.

OBJECTIVES: This study assessed the feasibility of both the delivery and evaluation of 'enhanced' (behaviourally informed) text message reminders containing links to existing co-designed resources supporting decision-making for people with severe mental illness (SMI) regarding attendance of cervical screening. DESIGN: A pilot randomised controlled trial (RCT). SETTING: 13 General Practice (GP) practices in London were recruited. PARTICIPANTS: GP practices identified people with SMI aged 24-64 years who were overdue cervical screening. Target sample size was 120 participants (60 per arm) based on existing guidance for pilot trials. INTERVENTION: In March 2025, participants were randomised (1:1) to receive either the enhanced (intervention) or the standard (control) SMS reminder. PRIMARY AND SECONDARY OUTCOME MEASURES: 18 weeks later, feasibility outcomes were collected (primary outcomes) and data analysis for a definitive RCT was rehearsed (secondary outcome). RESULTS: Of the 150 participants across 13 GP practices that were randomised (n=75 per arm), 132 (88%) texts delivered (intervention n=64/75 (85%), control n=68/75 (91%)). 10 practices (76.9%) provided follow-up data for 102 participants (intervention n=50, control n=52). Five participants (intervention n=4, control n=1) attended screening within the trial period. Participant survey response rate was low (9/132 (7%), intervention n=5, control n=4). Both SMS messages were low cost, with the intervention SMS a 50% higher cost to deliver (7.5p vs 5p per SMS). Primary feasibility measures of recruitment rate of GP practices (27%), retention of GP practices (77%) and participants (100%), SMS delivery (88%) and data completeness (64%) indicated viability, although survey response rate (7%) did not. CONCLUSIONS: Achieving adequate recruitment and retention, data completeness and comparable groups is viable with some amendments, although an alternative method is required to assess fidelity. Behaviourally informed SMS reminders are feasible to deliver to people with SMI, although it is uncertain if the extra resources are accessed and used. With changes to data collection, a definitive trial could be feasible. Given the low observed cervical screening attendance, additional intervention is needed for this group. TRIAL REGISTRATION NUMBER: ISRCTN12558681.

Humans↗

PubMed2026

A bimodal large language model reduces misalignment in patient education: A double-blinded randomized trial.

BACKGROUND: Effective patient education requires accurate communication aligned with patients' emotional and semantical needs. Text-based large language models (LLMs) lack access to non-verbal cues, which may contribute to misaligned responses. METHODS: We evaluated emotional and semantic misalignment in a text-based LLM using 64,200 utterances from 16,583 patient education cases across six departments and three centers. Dolphin was developed integrating text and audio cues and evaluated through emotion recognition, semantic consistency assessment, branch-level ablations, and a double-blinded randomized trial against a matched text-based LLM comparator (Chinese Clinical Trial Registry: (ChiCTR2500095933). FINDINGS: The text-based LLM showed emotional misalignment in 36.7% of responses and semantic misalignment in 28.3% of cases, with higher misalignment under greater burden. Dolphin outperformed the text-based LLM in emotion recognition accuracy (0.886 vs. 0.713) and semantic consistency (84.9% vs. 82.1%; both adjusted p < 0.001). Ablations supported contribution of audio branches. Dolphin received higher expert ratings than the text-based LLM and human educators (all p < 0.001). In 555 patients, Dolphin was associated with greater patient satisfaction (98.6% vs. 93.8%), suggestion acceptance (76.1% vs. 58.9%; p < 0.001), proactive disclosure (44.6% vs. 26.5%; p < 0.001), and fewer 7-day unplanned recontact (12.9% vs. 22.9%; p = 0.002). No unsafe recommendations or safety events were identified. CONCLUSIONS: Compared with text-based LLM, Dolphin improved emotional-semantic alignment and patient-education outcomes, supporting bimodal alignment as a strategy for reducing misalignment-driven communication failures. FUNDING: National Natural Science Foundation of China, State Key Laboratory Special Fund, and Chinese Academy of Medical Sciences Innovation Fund.

Humans↗

PubMed2026

Feasibility, Satisfaction, and Preliminary Efficacy Trial of text4FATHER for Engaging Expectant Fathers in Infant Care from Pregnancy to Early Infancy.

Engaging fathers perinatally improves infant outcomes and parent well-being, yet few strategies share evidence with fathers. We explored the feasibility, acceptability, and preliminary efficacy of text4FATHER-a texting intervention designed to improve fathers' infant care beliefs, self-efficacy, behaviors, and partner support from mid-pregnancy to 2 months post-birth. In this exploratory pilot randomized controlled trial, 97 adult expectant fathers with less than a college degree were randomized to receive text4FATHER or not. Self-reported outcomes by fathers and mothers were assessed at baseline (mid-pregnancy) and 2 months post-birth. We analyzed intent-to-treat effects using random coefficient regression models. We found recruiting expectant fathers feasible; of eligible father-mother dyads, 123/163 consented (recruitment feasibility = 68%). All intervention fathers (100%) reported being satisfied with text4FATHER; 100% of mothers of intervention fathers also reported satisfaction with the father getting texts. First-time fathers' antenatal attachment beliefs and coparenting support were higher in text4FATHER condition vs. control from baseline to 7-month follow-up; increases in first-time fathers' confidence in fathering and infant care were also observed-the latter finding was corroborated by partners of first-time fathers. text4FATHER is a promising intervention, particularly for first-time expectant fathers with lower educational levels who have no natural clinical or public health touchpoints. Its efficacy and effectiveness should be confirmed using larger and more diverse samples.

Confidence↗

PubMed2025

Artificial Intelligence in Diagnosing Depression Through Behavioural Cues: A Diagnostic Accuracy Systematic Review and Meta-Analysis.

AIM: To synthesise existing evidence concerning the application of AI methods in detecting depression through behavioural cues among adults in healthcare and community settings. DESIGN: This is a diagnostic accuracy systematic review. METHODS: This review included studies examining different AI methods in detecting depression among adults. Two independent reviewers screened, appraised and extracted data. Data were analysed by meta-analysis, narrative synthesis and subgroup analysis. DATA SOURCES: Published studies and grey literature were sought in 11 electronic databases. Hand search was conducted on reference lists and two journals. RESULTS: In total, 30 studies were included in this review. Twenty of which demonstrated that AI models had the potential to detect depression. Speech and facial expression showed better sensitivity, reflecting the ability to detect people with depression. Text and movement had better specificity, indicating the ability to rule out non-depressed individuals. Heterogeneity was initially high. Less heterogeneity was observed within each modality subgroup. CONCLUSIONS: This is the first systematic review examining AI models in detecting depression using all four behavioural cues: speech, texts, movement and facial expressions. IMPLICATIONS: A collaborative effort among healthcare professionals can be initiated to develop an AI-assisted depression detection system in general healthcare or community settings. IMPACT: It is challenging for general healthcare professionals to detect depressive symptoms among people in non-psychiatric settings. Our findings suggested the need for objective screening tools, such as an AI-assisted system, for screening depression. Therefore, people could receive accurate diagnosis and proper treatments for depression. REPORTING METHOD: This review followed the PRISMA checklist. PATIENTS OR PUBLIC CONTRIBUTION: No patients or public contribution.

Humans↗

PubMed2026

Automated CEAP Classification of Venous Duplex Reports Using Multimodal Artificial Intelligence.

OBJECTIVE: To develop and internally validate a prototype multimodal artificial intelligence system for automated CEAP (Clinical, Etiological, Anatomical and Pathophysiological) classification of venous duplex ultrasound (VDUS) reports, integrating natural language processing of free-text components with computer vision analysis of hand-drawn anatomical diagrams. METHODS: Single centre retrospective observational study using routinely collected clinical data. One thousand consecutive venous duplex ultrasound reports from Cambridge University Hospitals NHS Foundation Trust, UK (July 2024 - May 2025) were labelled according to the CEAP classification, excluding the Etiological component, which could not be reliably determined from duplex reports alone. Transfer learning was applied using ClinicalBERT for text and MobileNetV3 for diagrammatic data. Clinical classes were predicted from request line text. Text- and image-based pathophysiological models were developed for four anatomical territories (Great Saphenous Vein, Small Saphenous Vein, Deep system, Perforators), combined using late fusion with probability averaging. RESULTS: The clinical CEAP model achieved accuracy of 0.91, macro-F1 of 0.82, and macro-AUC of 0.98. Pathophysiological prediction varied, with text models broadly outperforming image models. Fusion yielded heterogeneous benefits, improving SSV performance but reducing Deep system accuracy. The performance of the final pathophysiological CEAP fusion models varied across anatomical territories: accuracy ranged from 0.70-0.92 and macro-AUC from 0.80-0.92. CONCLUSION: This study demonstrates the feasibility of automated CEAP classification from VDUS reports. Despite class imbalance affecting minority class predictions, the strong discriminatory performance validates this multimodal ML model for extracting clinically meaningful information from real-world data. This approach offers potential, pending external validation, to streamline vascular services through automated triage and guideline-compliant decision making.

Artificial intelligence↗

PubMed2026

Digital healthcare solutions in preoperative care: A systematic review.

OBJECTIVE: Active participation in preoperative anesthesia preparation is crucial to ensure safe and efficient care. Compliance with preoperative instructions improves clinical outcomes, enhances patient satisfaction and optimizes use of healthcare resources. As digital communication becomes increasingly integrated into healthcare, interactive digital tools such as smartphone applications and Short Message Service (SMS) reminders may offer a valuable means of engaging patients in their own care. In this review, we evaluated the role of digital tools in guiding patients during their preoperative care pathway for anesthesia. METHODS: Following registration (CRD420250655119), we conducted a systematic review of studies evaluating the use of smartphone applications or SMS reminders designed to support preoperative preparation for anesthesia or procedural sedation in adult patients undergoing elective procedures. The primary outcome was compliance with preoperative instructions. Secondary outcomes included rate of late cancellations, patient satisfaction and cost-effectiveness. Studies were eligible if they reported at least one of these outcomes. RESULTS: Ten studies (1 RCT and 9 observational studies), including 11501 participants, were identified. Compliance with preoperative instructions was assessed in 8 studies, most of which reported higher compliance in patients receiving digital interventions across multiple instruction domains, although statistical significance was not consistently observed. Evidence suggested a beneficial effect on reducing late cancellations and improving patient satisfaction. However, results varied across study designs, and data on cost-effectiveness were limited. CONCLUSIONS: Digital tools for preoperative anesthesia guidance were associated with higher compliance and showed potential reduction of late cancellations and increase of patient satisfaction. However, the current evidence is predominantly observational and heterogeneous, limiting the strength of conclusions. PRACTICAL IMPLICATIONS: With healthcare systems under pressure, digital technologies may offer a scalable and patient-centered care solution to support preoperative anesthesia preparation. Nonetheless, further high-quality research is needed to evaluate their long-term clinical, economic and equity implications.

Humans↗

PubMed2026

Effect of a digitally augmented general health promotion intervention on abstinence from health-risk behaviors among emergency department discharge patients: A randomized controlled trial.

BACKGROUND: Noncommunicable diseases (NCDs) are the leading global cause of death and are driven by modifiable behaviors, such as tobacco use, harmful alcohol consumption, unhealthy diet, and physical inactivity. Recognizing that emergency department (ED) visits represent a unique opportunity to promote behavior change, this trial evaluated a digitally augmented, theory based general health promotion approach, combining a brief telephone-based intervention with mobile instant messaging support, to help discharged ED patients abstain from health risk behaviors. METHODS AND FINDINGS: This assessor-blinded randomized controlled trial was conducted in a major public hospital ED in Hong Kong. Adults (18-65 years) triaged as semi-urgent or non-urgent and with ≥1 health-risk behavior and smartphone access were randomized to receive a digitally augmented, theory‑based general health‑promotion intervention consisting of a brief telephone‑based AWARD‑model intervention (Ask, Warn, Advise, Refer, and Do-it-again) followed by weekly WhatsApp or WeChat messages for 6 months, or to a control group receiving brief telephone advice only. The primary outcome was self-report abstinence from ≥1 health-risk behavior at 6 months; secondary outcomes included the proportion of participants who achieved self-reported abstinence from ≥1 health-risk behavior at 12 months and reduction in the number of behaviors at 6 and 12 months. Of the 2,134 screened patients, 572 were enrolled (286 per group). At 6 months, 30.1% of the intervention participants versus 19.9% of the controls achieved self-reported abstinence (RR = 1.51; 95% CI, 1.13-2.02; P = 0.006). The intervention also significantly increased the likelihood of fewer risky behaviors at 6 (RR = 1.54; P = 0.01) and 12 (RR = 1.48; P = 0.02) months. Physical inactivity showed the greatest improvement at 6 months (31.7% versus 16.2%; P < 0.001). The effects attenuated after cessation of booster messaging. Limitations include reliance on self-reported outcomes, the single-center study design, and loss to follow-up, which may have affected the generalizability of the results. CONCLUSIONS: A digitally augmented, theory-based general health promotion strategy delivered at ED discharge through brief telephone intervention and mobile instant messaging support demonstrated short-term benefits in promoting self-reported abstinence and reducing health-risk behaviors at 6 months. However, the absence of a sustained effect at 12 months suggests that extended support or maintenance strategies may be required to maintain these improvements over time. Multicenter trials with longer follow-up are warranted to evaluate long-term effectiveness. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov (Registration No: NCT06077565).

Humans↗

PubMed2026

Teaching Acute Coronary Syndrome High-Risk ECG Interpretation and Clinical Decision-Making Through FOAMed Videos and Podcast Versus Print-Based Materials Among Emergency Care Providers: Randomized Controlled Mixed Methods Trial.

BACKGROUND: Accurate interpretation of high-risk acute coronary syndrome (ACS) electrocardiograms (ECGs) is essential for early diagnosis and timely reperfusion, yet substantial deficits persist across health care professions. Digital self-learning formats such as FOAMed (Free Open Access Medical Education) are widely used, but their effectiveness has rarely been evaluated for complex, high-risk ACS ECG patterns. Existing ECG education studies often focus on students or single professional groups and established ST-segment elevation myocardial infarction (STEMI) criteria, leaving newer guideline-recognized STEMI equivalents, selected emerging occlusion myocardial infarction (OMI)-related patterns, and interprofessional emergency care underrepresented. OBJECTIVE: This study aimed to compare the effectiveness of FOAMed podcast and videos versus traditional print-based materials for teaching high-risk ACS ECG patterns and related clinical decision-making in emergency providers. METHODS: We conducted a prospective, interprofessional, controlled mixed methods trial across 5 training sites in Germany. Paramedics, prehospital emergency physicians, and emergency department clinicians received either a FOAMed multimedia module or print-based materials through concealed allocation; deviations from the intended 1:1 ratio resulted from participant no-shows. The intervention consisted of a 30-minute supervised self-learning session. In total, 103 participants were allocated to FOAMed (n=45) or print-based materials (n=58). Two coprimary outcomes were assessed: ECG interpretation accuracy and text-based ACS clinical decision-making. Secondary outcomes included subjective confidence, learning experience, and exploratory qualitative free-text responses. Outcome assessment was automated and blinded; mixed ANOVA was the primary analysis. The study was not prospectively registered because it assessed educational outcomes in health care professionals rather than patient health outcomes. RESULTS: All 103 participants completed the study. Both groups improved, with greater gains in the FOAMed group: ECG interpretation increased from 55% to 65.5% and text-based ACS clinical decision-making from 45% to 68%, versus 57% to 60% and from 47% to 63%, respectively, in the print-based group. Effect sizes were η²=0.055 for ECG interpretation and η²=0.044 for clinical decision-making. Exploratory subgroup analyses provided no evidence of differential effects across age, gender, or professional background and were likely underpowered. Qualitative responses (46 and 37 entries) provided contextual insights into perceived clarity, engagement, and practical relevance supporting the quantitative findings. CONCLUSIONS: This study is innovative in directly comparing a curated FOAMed multimedia module with selected print-based materials in an interprofessional emergency care population. It differs from existing research by focusing on subtle, emerging ischemic patterns and evaluating realistic, time-limited self-learning formats. The findings provide evidence that curated FOAMed resources can produce greater short-term improvements in ECG interpretation and text-based ACS clinical decision-making than traditional print-based materials in this setting. Although implications for clinical performance remain hypothetical, concise, high-quality digital modules may represent a practical supplement to structured continuing education in emergency care.

Humans↗

PubMed2026

Health risk assessment of inorganic arsenic: an umbrella review.

Inorganic arsenic (iAs) is a toxic environmental pollutant linked to serious health risks, prompting global regulatory efforts. This study identifies major health conditions associated with iAs exposure using text network analysis, and assesses health risk assessments through an umbrella review and dose-response analysis. It synthesizes previous systematic reviews to offer a broader perspective on iAs-related health effects. An optimized text network analysis-based search strategy was applied across multiple databases to identify relevant systematic reviews. An umbrella review framework was employed to synthesize and reinterpret findings across systematic reviews. The methodological quality of included systematic reviews was assessed using the A MeaSurement Tool to Assess systematic Reviews 2 tool. Extracted data on study characteristics, exposure levels, and risk estimates were analyzed to evaluate the dose-response relationship between iAs exposure and health outcomes. From 922 systematic reviews, 36 were included and categorized into 10 health condition groups. For example, seven SRs found a significant dose-response relationship between iAs and bladder cancer, with one systematic review reporting relative risks of 2.70, 4.20, and 5.80 at 10, 50, and 150 µg/L, respectively. Individual study analysis further showed that each 10 µg/L increase in iAs raised bladder cancer risk by 3.11 % (p=0.003). iAs exposure is associated with hypertension, diabetes, cardiovascular disease, and adverse fetal outcomes. Dose-dependent increases in bladder cancer, lung cancer, and hypertension risks were observed. These findings support more precise health risk assessments and regulatory strategies.

Humans↗

PubMed2026

Men's experiences of multiple long-term conditions and/or disability in the UK Game of Stones weight management trial: a mixed-methods evaluation.

OBJECTIVES: To explore experiences, health outcomes and retention of men with multiple long-term conditions (MLTCs) and/or disability within the Game of Stones weight management randomised controlled trial (RCT). DESIGN: Mixed-methods process evaluation within an RCT where secondary outcomes included the Weight Self-Stigma Questionnaire, EuroQol 5-Dimension 5-Level (EQ-5D-5L), EQ-5D-5L anxiety and depression subscale, Patient Health Questionnaire-4 and retention. Semistructured interviews were conducted at 12 months and analysed using the framework method. SETTING: Conducted across three UK trial centres: Belfast, Bristol and Glasgow. PARTICIPANTS: 585 men with obesity (mean (SD) age, 50.7 (13.3) years) were randomised to one of three groups: behavioural text messages with financial incentives, texts alone or waiting-list control. Interviews were conducted with 54 participants from the two intervention groups. RESULTS: 235 (40%) participants lived with MLTCs, 181 (31%) had a single condition, 167 (29%) had no conditions and 165 (29%) had a disability. Of those with MLTCs, 99 were disabled and 93 were living in deprived areas. Participants with MLTCs and/or disability were older, fewer had a degree-level qualification and fewer were in full-time work. Retention at 12 months was higher for men with disability (76%) or no long-term conditions (75%) and lower for men with diabetes (65%). Self-reported weight stigma, well-being and quality-of-life scores improved or stayed the same for men living with MLTCs in the intervention groups; however, results for anxiety and depression screening scores were inconsistent. Participant experiences indicated complex dynamic health, social and life situations which could provide motivation to lose weight for some but not others. Hospitalisation and poor mobility, with inability to exercise, were demotivating for making changes to reach weight loss targets. CONCLUSIONS: Men living with MLTCs and/or disability varied from very successful weight loss and improved health to not prioritising or feeling helped by the programme or disengagement due to immobility or diabetes. TRIAL REGISTRATION NUMBER: isrctn.org Identifier: ISRCTN91974895.

Humans↗

PubMed2026

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry↗

PubMed2025

Financial Literacy Skills Instruction Among Autistic Individuals: A Systematic Review.

PURPOSE: Financial literacy skills are crucial for an independent life in modern societies. However, it does not appear that researchers have examined financial literacy skills among autistic individuals. This manuscript uses a systematic review to identify existing research which examines financial literacy skill instruction for autistic individuals. METHOD: We used a systematic review strategy to identify approximately 9500 articles. These articles proceeded through abstract and full-text screening for relevance. RESULTS: We identified two studies which directly taught financial literacy skills, and ten more which taught more basic money skills (such as calculating change). Neither of the two studies which taught financial literacy skills did so as an exclusive focus; both taught these skills alongside other objectives, as part of a larger intervention. CONCLUSIONS: Research on financial literacy skill instruction among autistic individuals is lacking, though there is a foundation of research examining money skills and related life skills to build upon. We recommend additional research on financial literacy skill instruction, ideally designed with the unique skills and needs of autistic individuals in mind, and with their input.

Humans↗

PubMed2026

Analysis of deep learning techniques in computer-aided diagnosis for meniscus injuries: a systematic literature review.

Meniscus informatics is a growing subject of study in the healthcare industry. One of the major hindrances to the healthcare system's transformation is obtaining knowledge and meaningful information from complicated, high-dimensional and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, dissimilar, poorly documented, and generally unstructured electronic health records, imaging, sensor data and text, even after many current techniques have been used to extract more robust and useful elements from the data for analysis. New efficient standards for building end-to-end learning models from complex data are therefore needed. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for diagnosing meniscus tears and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to shortcomings and the need for better technique development, and we provide new perspectives about this exciting new development in the field.

Humans↗

PubMed2026

Messaging Strategies for Tobacco Prevention and Cessation Among People with Depression: A Scoping Review.

INTRODUCTION: Depression is strongly associated with higher tobacco use and lower quit rate; few communication campaigns have been designed with these mental health factors in mind. This scoping review compiles existing research on tobacco prevention and cessation messaging involving people with depression to identify gaps and opportunities for future message development. METHODS: Sources included PubMed, PsycINFO, Scopus, Academic Search Premier, and ProQuest Central (November - December 2024). The 55 studies included examined tobacco prevention or cessation messages and measured depression, depressive symptoms, or mental health as a primary outcome or analytic covariate. Study characteristics, target population, delivery format, message content, theoretical frameworks, outcomes, and gaps were extracted. RESULTS: RCTs made up half (51%) of the included studies, and most (78%) were conducted in the U.S. Nearly half (46%) required participants to have a mental health condition. Interventions most often used interactive (65.5%) or text-based (47.3%) communication and focused on tobacco cessation (89%) rather than vaping (9%). Common outcomes included feasibility or acceptability (37.7%) and point prevalence abstinence (37.7%). Mental health-specific messages showed mixed effectiveness. CONCLUSIONS: Despite progress in integrating mental health into tobacco messaging, targeted interventions for people with depression remain limited. Few studies tested long-term outcomes or used biochemical verification; many relied on untargeted generalized messaging.

Journal Article↗

PubMed2026

Methods for defining equity-stratifying variables: a systematic review of validation studies.

BACKGROUND AND OBJECTIVE: Disease burden is often disproportionally higher among those who are socially disadvantaged by factors defined in the PROGRESS-Plus framework (ie, Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, and Social capital, with "Plus" covering features like age and disability). The accuracy and applicability of case definitions to identify these variables from administrative and clinical health data are unknown. We conducted a systematic review to explore how equity-stratifying variables, as categorized by the PROGRESS-Plus framework, have been defined and validated in epidemiologic studies using administrative health, population-level, or electronic health record (EHR) data. METHODS: Medline, EMBASE, CINAHL, Web of Science, and Google Scholar were searched from the inception of the databases to 2024 for validation studies of equity-stratifying variables in adults using administrative health datasets, health registries, or EHR data. Titles and abstracts, followed by relevant full-text articles, were screened in duplicate by two reviewers for eligibility. The data sources utilized, algorithms employed, and their associated performance measures were extracted and synthesized from included studies. Given substantial heterogeneity in study design, equity-stratifying variable definition, and performance metrics, meta-analysis was not possible. RESULTS: Of the 9099 unique citations screened, 188 full texts were reviewed and 116 were included in this review. Most studies were published between 2019 and 2024 (n = 64, 55%) and were validation studies of race/ethnicity definitions that used race/ethnicity codes or surname list algorithms (n = 66, 57%). No studies examined religion. Regarding the reported performance measure estimates, the race/ethnicity/culture/language equity-stratifying variables category had the largest variability across sensitivity, positive predictive value (PPV), and Cohen's Kappa. Occupation validation studies had the lowest variation in sensitivity and PPV. CONCLUSION: Despite an increasing number of publications reporting on the validation of equity-stratifying variables relevant to the PROGRESS-Plus framework, performance measures varied widely across studies. The significant heterogeneity in equity-stratifying variable definitions and methods used to validate them support the need for further rigorous validation of equity-stratifying variables in administrative and clinical health data. PLAIN LANGUAGE SUMMARY: Disease burden is often higher in people who experience financial hardships, lower level of education, discrimination due to race/ethnicity, and unstable housing. These social factors can be considered health equity factors and are important for understanding health inequalities. Health researchers often use large datasets, such as hospital or electronic health records (EHRs), to study these health equity factors. However, it is not clear how accurately these data sources capture information about people's social circumstances and how these factors are defined. In this study, we reviewed existing research to understand how health equity factors have been defined across health data sources and how accurate they are at measuring aspects of health equity and social disadvantage. Of the more than 9000 studies we identified, we included 116 that met our criteria for this systematic review. Most included studies focused on identifying race and ethnicity, often using codes or surname-based methods. We found that the accuracy of these methods varied widely across studies, meaning results may not always be reliable or comparable. Overall, our findings show that there are inconsistencies in how social factors are defined and measured in health data. This makes it difficult to fully understand and address health inequalities using routinely collected health data. More work is needed to develop and validate better quality and more consistent methods for capturing these important social factors.

Humans↗

PubMed2026

Association between packed red blood cell transfusion and clinical deterioration in neonatal necrotizing enterocolitis: a systematic review and meta-analysis.

BACKGROUND: No systematic review has evaluated the existing evidence regarding the association between packed red blood cell (pRBC) transfusion and clinical worsening of necrotizing enterocolitis (NEC) in neonates. This systematic review and meta-analysis was conducted to address this knowledge gap. MATERIALS AND METHODS: We searched the Cochrane Library, EBSCO, Embase, Web of Science, Google Scholar, and PubMed for studies on pRBC transfusion and NEC published before May 10, 2025. Relevant articles were selected through title, abstract, and full-text screening. English-language case-control studies or cohort studies, or randomized controlled trials involving newborns with NEC that compared pRBC transfusion with no transfusion and reported changes in NEC clinical status were included. Review articles, systematic reviews, case reports, editorials, animal studies, duplicate publications, and studies with incomplete data were excluded. RESULTS: Five studies involving 971 neonates with NEC were included. The pooled analysis demonstrated a potential association between pRBC transfusion and clinical deterioration of NEC in neonates (odds ratio: 6.05, 95% confidence interval: 3.02-12.14). CONCLUSIONS: pRBC transfusion was associated with an exacerbation of NEC in neonates. However, these findings should be interpreted cautiously because of the small number of eligible studies included in this meta-analysis, and future large-scale, well-designed studies are needed to confirm the observed association.

Humans↗