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PubMed2026

The Childhood Cancer and Leukemia International Consortium (CLIC): Expanding global collaboration in pediatric cancer etiology research.

Childhood cancers are rare, but incidence has risen modestly in countries with robust registration, partly reflecting improved diagnosis. In high-income countries, cancer is the leading cause of disease-related death in children. Marked inequities in incidence, survival, and research capacity underscore the need for large-scale collaboration to identify environmental, genetic, and contextual determinants of risk. The Childhood Cancer and Leukemia International Consortium (CLIC) was established in 2007 to study the etiology of childhood leukemia and later expanded in 2019 to include other childhood cancers, principally solid tumors. CLIC pools harmonized, individual-level data from case-control and cohort studies, obtained through interviews, record linkage (insurance claims, registries), or geographic information systems, and integrates germline genomic data where available. Membership has grown from 13 studies in 9 countries to 57 studies in 21 countries; recruitment spans the early 1960s to the present and encompasses approximately 150,000 cases across all tumor types and 300,000 controls with clinical, demographic, and exposure data, centralized via harmonized data dictionaries at the Data Coordination Center, established in 2014 at the International Agency for Research on Cancer, and supported by a secure analysis platform. Pooled analyses across diverse populations have implicated parental age, prenatal vitamin or folic acid use, mode of delivery, fetal growth, selected congenital anomalies, occupational or household exposures (e.g., pesticides), paternal smoking, and markers of early-life immune modulation (e.g., breastfeeding, daycare attendance) in leukemia risk, informing carcinogen evaluation and prevention. The integration of genetic ancestry and germline susceptibility data is clarifying ancestry-related differences in leukemia biology and outcomes, while confirming risk loci with population-specific effects. CLIC is now adding polygenic risk scores and exposomic data to refine etiologic subtyping and identify modifiable pathways, while broadening representation from underserved regions through partnership-building and capacity-strengthening.

Humans↗
PubMed2026

Care Navigation for Methamphetamine Use Disorder: A Randomized Clinical Trial.

IMPORTANCE: Stimulant-involved deaths continue to increase in the US, and methamphetamine use remains a weighty public health concern. Treating methamphetamine use disorders is complicated. Contingency management has demonstrated the best effectiveness but is not widely implemented. OBJECTIVE: To examine the effectiveness of dedicated care navigation in linking patients to treatment. DESIGN, SETTING, AND PARTICIPANTS: This prospective randomized clinical trial was conducted at an integrated safety-net health system in Denver, Colorado, between April 10, 2023, and December 31, 2024. Eligible participants were 18 years or older who had a methamphetamine-related encounter in an acute care setting; those with involuntary treatment holds, substance treatment in past 90 days or actively seeking treatment, and inability to provide consent were excluded. Participants completed baseline, 30-day, and 90-day study visits. INTERVENTION: Dedicated care navigation, incorporating contingency management principles, with a focus on addressing health-related social needs. MAIN OUTCOMES AND MEASURES: Linkage to treatment within 30 and 90 days of enrollment defined as a composite measure of at least 1 of the following: electronic health record data indicating a visit at the health system's substance treatment clinic, a behavioral health encounter at an outpatient clinic, temporary residential treatment, or self-reported treatment on the 30- and/or 90-day follow-up survey. RESULTS: Of 192 participants enrolled in the Beginning Early and Assertive Treatment for Methamphetamine Use trial, 156 (81.3%) were male, and the median age was 39 (IQR, 31-47) years. Most participants were unstably housed (163 [84.9%]), not currently employed (158 [82.3%]), and without regular access to a working phone (94 [49.0%]). Of the 96 participants randomized to the intervention, 60 (62.5%) engaged in 2 or more navigation sessions, 45 (46.9%) completed the 30-day study visit, and 47 (49.0%) completed the 90-day study visit compared with 44 (46.3%) and 37 (38.5%), respectively, of the 96 randomized to the control arm. No statistically significant differences in treatment linkage were observed at 30 days (24 participants [25.0%] in both arms; risk ratio, 1.00 [95% CI, 0.61-1.63]) or 90 days post enrollment, (32 [33.3%] in intervention vs 24 [25.0%] in control arms; risk ratio, 1.33 [95% CI, 0.85-2.09]). CONCLUSIONS AND RELEVANCE: In this randomized clinical trial, integrating principles of contingency management into the intervention may have increased engagement with a dedicated care navigator but did not increase likelihood of linkage to treatment for methamphetamine use disorder. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT06033365.

Humans↗
PubMed2026

Pre-clinical evaluation of the anticaries effect of an experimental Malva sylvestris extract mouthwash using a cariogenic model in situ.

OBJECTIVE: The aim of this study was to evaluate the antimicrobial and anticariogenic potential of Malva sylvestris extract on enamel and dentin in situ. METHODS: A double-blind crossover in situ study was conducted with 12 participants wearing palatal appliances containing two bovine enamel and two dentin specimens per 3 phases, a total of 72 enamel and dentin specimens. Biofilm formation and daily sucrose exposure were allowed. Treatments were applied twice daily in three phases: Malva sylvestris (2.5%, MS); fluoride (225 ppm, F); and placebo (P). After seven days, biofilm was collected from the bovine specimens for analysis of Lactobacillus spp. and mutans streptococci by Colony Forming Unit counts (CFU log₁₀/mL). Dental demineralization of the bovine specimens was assessed by transverse microradiography (TMR). RESULTS: MS did not reduce Lactobacillus spp. counts (CFU log₁₀/mL: enamel 6.63±0.81; dentin 6.68±0.92) compared to P (6.63±0.70; 6.62±0.51). F also did not differ (6.29±0.75; 6.32±0.41; ANOVA/Tukey, p>0.38). Mutans streptococci data were inconclusive. In enamel, both MS (2320.8±768.2 %vol·µm; 101.6±27.0 µm) and F (1777.3±733.3 %vol·µm; 95.8±23.5 µm) significantly reduced integrated mineral loss and lesion depth compared to P (3517.2±1119.9 %vol·µm; 138.6±19.5 µm; ANOVA/Tukey, p≤0.0003). In dentin, MS significantly reduced integrated mineral loss (322.5 [250-580] %vol·µm) and lesion depth (30.1 [15-42.2] µm) compared to P (880 [580-1705]; 58.3 [32.2-88.6] µm; Kruskal-Wallis/Dunn, p≤0.001), while F (587.5 [305-720]; 25.2 [16.5-38.8] µm) did not differ significantly (p>0.05). CONCLUSIONS: Malva sylvestris extract had no antimicrobial effect on Lactobacillus spp. counts, but significantly reduced enamel and dentin demineralization, showing anticaries effect comparable to fluoride. CLINICAL RELEVANCE: Malva sylvestris has demonstrated promising biological activity. This study investigates the antimicrobial efficacy of Malva sylvestris against cariogenic microorganisms in situ. Our findings provide relevant evidence that M. sylvestris exert significant anticaries effects using an in situ model.

Biofilms↗
PubMed2026

Emerging Principles in Spatial Functional Genomics.

Spatial transcriptomic and proteomic atlases have enabled mapping of gene programs within intact tissues, but these measurements remain largely descriptive and do not define the mechanisms controlling tissue biology. Pooled CRISPR screening provides scalable causal interrogation of gene function but remains largely confined to dissociated systems that lack spatial context. In vivo spatial functional genomics (SFG) bridges these approaches by integrating genetic perturbations with in situ transcriptomic and proteomic readouts to measure gene function within intact tissue ecosystems. By preserving spatial organization, SFG enables interpretation of perturbations through effects on cell-cell interactions, diffusible signals, multicellular niches, and tissue architecture. Here, we outline key design axes of SFG: perturbation strategy, barcoding strategy, and phenotypic readout. We discuss computational challenges, including spatial autocorrelation, neighborhood dependence, and context-aware null modeling, and highlight how SFG reveals non-cell-autonomous, architecture-dependent mechanisms of gene function, advancing toward predictive models of tissue organization and gene function.

Genomics↗
PubMed2026

The landscape of pruning for large language models: A systematic review and unified taxonomy.

Confronting the inherent tension between the exceptional capabilities and the immense computational costs of Large Language Models (LLMs), pruning has become a crucial technique for achieving efficient deployment. However, a systematic analytical framework dedicated specifically to LLM pruning remains absent. In this paper, we aim to bridge this gap. We first elucidate the theoretical foundations that underpin the effectiveness of pruning, namely overparameterization and redundancy, and then propose a multidimensional taxonomy that organizes existing approaches along the axes of granularity, timing, and criteria. Building upon this unified perspective, we further analyze performance recovery mechanisms and the broader evaluation ecosystem, while also exploring forward-looking challenges such as interpretability, automation, and hardware-algorithm co-design. Through this comprehensive synthesis, we seek to provide an integrated and coherent analytical lens for advancing both research and practice in LLM pruning.

Large Language Models↗
PubMed2026

Exploring Professional Experiences in Caring for Vulnerable Migrants in an Italian Rural Reception Centre: A Qualitative Study Using Multidimensional Textual Analysis-Professional Experiences in Rural Migrant Care.

AIM: This study aims to explore the experiences, strengths, challenges, and potential improvements for professionals in managing the complex needs of vulnerable migrants (VM) in an Italian rural reception centre. METHODS: A qualitative study using semi-structured interviews was conducted in April 2024. Data were analysed using the Automatic Analysis of Textual Data, based on Fraire's seven-step model for Exploratory Multidimensional Data Analysis. DATA SOURCES: Data were collected from 16 professionals working in a rural reception centre in southern Italy. Interviews were conducted and analysed using AATD in April 2024. FINDINGS: The analysis identified two main dimensions of professionals' roles: balancing systemic responsibilities with personal engagement and managing immediate needs versus long-term integration goals. Professionals face significant challenges, such as resource scarcity, bureaucratic inefficiencies, and emotional fatigue, which impact their well-being and the quality of care provided to migrants. Resilience, adaptability, and multidisciplinary collaboration were identified as key strengths. CONCLUSION: The study highlights the dual nature of professionals' work in reception centres, requiring them to balance operational tasks with emotional involvement in migrant care. Targeted interventions and systemic reforms are necessary to support professionals and enhance the quality of care for vulnerable migrants, particularly in resource-constrained rural settings. IMPLICATIONS FOR PRACTICE AND/OR PATIENT CARE: This study underscores the importance of providing targeted support to professionals working in reception centres, including training in intercultural competence, stress management, and coping strategies. Policies should address systemic challenges and provide resources to enhance healthcare delivery and social integration programs. REPORTING METHOD: This study adhered to the EQUATOR guidelines for reporting qualitative research (COREQ). The findings were reported in compliance with these guidelines, ensuring methodological rigour and transparency. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: This study highlights the critical need for targeted support and training for professionals working in reception centres, particularly in rural settings. To improve care for vulnerable migrants, professionals should receive training in intercultural competence, stress management, and coping strategies to better navigate the complex challenges they face. Furthermore, systemic changes are necessary to alleviate the pressures on reception centres, such as streamlining bureaucratic processes and enhancing healthcare infrastructure, particularly in rural areas where resources are limited. By addressing these needs, we can improve the well-being of both the professionals and the migrants they serve, fostering more effective support systems and better care outcomes. Additionally, fostering multidisciplinary collaboration and community engagement can contribute to more comprehensive and sustainable care models. PROTOCOL REGISTRATION: The Ethics Committee of the University of Rome Tor Vergata approved this study on 07/07/2021 (protocol registration number 160.21).

Humans↗
PubMed2026

Hierarchical modeling of tumor subtypes in cell lines using large-scale genomic datasets.

Cancer cell lines (CLs) are widely used to study tumor biology and drug response, yet their translational relevance is often limited by inaccurate subtype annotations. Existing CL-tumor matching approaches are frequently constrained by flat classification schemes, weak subtype definitions, and the exclusion of normal tissue references, leading to potential confounding of tumor-specific and tissue-of-origin signals. To address these limitations, a hierarchical classification (HC) framework is presented in which CLs are aligned with patient tumors across biological resolutions, from organ to molecular subtype. Gene expression profiles from 802 CLs, 5,612 tumors from The Cancer Genome Atlas (TCGA) , and 8,939 non-cancerous tissues were integrated to separate oncogenic signals from tissue-specific signals. Node-specific features were selected using maximum relevance minimum redundancy, and balanced accuracies of 89% in cross-validation and 75%, and 80% on external datasets were achieved. Through the framework, 43 CLs were reassigned, and clinically relevant underrepresented subtypes were identified.

cancer cell lines↗
PubMed2026

Mapping antibody sequences and effector functions across spatial niches.

Antibodies are fundamental to human health but can also drive pathology. Each antibody has a molecular specificity, encoded by their clonally heritable B cell receptor (BCR). Recent advances in spatial transcriptomics coupled with repertoire sequencing have enabled capturing antibody-secreting cells (ASCs) and their clonal BCR within their tissue microenvironment. However, our understanding of antibody production niches remains limited. Furthermore, where antibodies are produced can be distinct from where antibodies exert their effector function. Here, we propose a conceptual spatial framework to distinguish between 'antibody production niches', defined by the ASC, BCR, and niche composition, versus 'antibody functional niches', composed of the antibody, antigen, and effector landscape. We then examine the possibilities and challenges to map and link antibody-encoding sequences and antibody effector functions using current and emerging technologies. Combined, we argue that integrating spatial sequence data with the antibody functional context is essential to decode the architecture of antibody-mediated immunity.

Humans↗
PubMed2026

Nurse-Led Home-Based Mobile Health Cardiac Rehabilitation Program for Patients With Chronic Heart Failure: A Randomized Controlled Trial.

This 12-week randomized controlled trial evaluated a nurse-led mHealth intervention for patients with chronic heart failure, conceptually informed by Riegel's middle-range theory of self-care of chronic illness. The program integrated wearable activity tracking with weekly nurse-led behavioral coaching, reflecting the core self-care processes of monitoring, maintenance, and management. Compared with usual care, the intervention significantly improved daily step count, 6-minute walk distance, metabolic equivalents, and left ventricular ejection fraction. Findings highlight the effectiveness of theory-informed, nurse-delivered mHealth strategies in enhancing physical activity and cardiopulmonary function, while underscoring the critical role of advanced practice nurses in home-based chronic disease management.

Aged↗
PubMed2026

Multimodal alignment improves generalizability of genomic biomarker prediction in computational pathology.

Computational pathology models that use digitized histopathology whole-slide images have the potential to become a cost-effective and scalable alternative to molecular assays for the prediction of genomic biomarkers, a key task in precision oncology. However, as new genomic biomarkers are discovered or quantified, large, labeled datasets must be prospectively collected to train new models. To address this challenge, we developed multimodal alignment for biomarker learning and generalization (MARBLE), a multimodal contrastive pretraining strategy that integrates structured biomarker knowledge into representation learning of histopathology images. MARBLE aligns histopathology-derived representations with representations of genomic biomarkers generated by a large language model (LLM) and a protein language model (PLM). This biologically informed alignment enables data-efficient generalization to novel, out-of-distribution biomarkers. Using the MSK-IMPACT cohort of over 40,000 patients across multiple biomarker panel versions, we design experiments grounded in real-world data to demonstrate the value of our proposed approach.

CP: computational biology↗
PubMed2026

The science of Arabic coffee (Qahwa): from phytochemistry and nutritional profile to health benefits and safety evaluation.

Arabic coffee (Qahwa), a traditional beverage widely consumed in the Middle East, has attracted increasing scientific attention due to its distinctive phytochemical composition and associated health effects. This review provides an integrated analysis of Qahwa's nutritional profile, focusing on its key bioactive constituents, including chlorogenic acids, caffeine, diterpenes (cafestol and kahweol), and phenolic compounds. These constituents contribute to a range of biological activities, notably antioxidant, anti-inflammatory, hepatoprotective, and metabolic regulatory effects. The influence of technological variables, including roasting degree, brewing method, and bean origin, on the chemical composition and functional properties is critically examined. Safety concerns, particularly acrylamide formation and mycotoxin contamination, are also discussed. Although emerging data support Qahwa's potential as a functional beverage, further research is required to clarify dose-response relationships, synergistic interactions, and long-term health outcomes. This work highlights Qahwa as a promising candidate for food and nutraceutical applications, warranting standardized compositional profiling and toxicological evaluation.

Humans↗
PubMed2026

Comprehensive quality profiling and comparative metabolic characterization of seven dominant fresh-eating Chinese olive (Canarium album Lour.) cultivars in Southern China.

Fresh-eating Chinese olive (Canarium album Lour.) is a subtropical fruit endemic to southern China with considerable commercial value, yet systematic quality characterization of dominant cultivars remains scarce. This study established a multi-dimensional quality dataset for seven dominant cultivars from Fujian and Guangdong provinces, integrating nutritional components, soluble sugars, organic acids, mineral elements, volatile profiles, and non-targeted metabolomics. Significant cultivar-specific differences were observed across all evaluated dimensions: "Lingfeng" exhibited a sugar-dominant low-acid profile, whereas "Sanleng" showed elevated phenolic constituents accumulation. Volatile profiling identified terpenoid-based candidate discriminatory biomarkers, and metabolomic analysis revealed phenylpropanoid biosynthesis, tryptophan metabolism, and starch and sucrose metabolism as the most variable pathways. Correlations between untargeted profiling and targeted absolute quantification validated untargeted result reliability and revealed their complementarity in nutritional evaluation. These findings provide baseline data for FECO germplasm evaluation and targeted industrial utilization.

China↗
PubMed2026

From fear to empowerment: the impact of employees AI awareness on workplace well-being - a new insight from the JD-R model.

PURPOSE: The primary purpose of the study was to explore the impact of health workers' awareness of artificial intelligence (AI) on their workplace well-being, addressing a critical gap in the literature. By examining this relationship through the lens of the Job demands-resources (JD-R) model, the study aimed to provide insights into how health workers' perceptions of AI integration in their jobs and careers could influence their informal learning behaviour and, consequently, their overall well-being in the workplace. The study's findings could inform strategies for supporting healthcare workers during technological transformations. DESIGN/METHODOLOGY/APPROACH: The study employed a quantitative research design using a survey methodology to collect data from 420 health workers across 10 hospitals in Ghana that have adopted AI technologies. The study was analysed using OLS and structural equation modelling. FINDINGS: The study findings revealed that health workers' AI awareness positively impacts their informal learning behaviour at the workplace. Again, informal learning behaviour positively impacts health workers' workplace well-being. Moreover, informal learning behaviour mediates the relationship between health workers' AI awareness and workplace wellbeing. Furthermore, employee learning orientation was found to strengthen the effect of AI awareness on informal learning behaviour. RESEARCH LIMITATIONS/IMPLICATIONS: While the study provides valuable insights, it is important to acknowledge its limitations. The study was conducted in a specific context (Ghanaian hospitals adopting AI), which may limit the generalizability of the findings to other healthcare settings or industries. Self-reported data from the questionnaires may be subject to response biases, and the study did not account for potential confounding factors that could influence the relationships between the variables. PRACTICAL IMPLICATIONS: The study offers practical implications for healthcare organizations navigating the digital transformation era. By understanding the positive impact of health workers' AI awareness on their informal learning behaviour and well-being, organizations can prioritize initiatives that foster a learning-oriented culture and provide opportunities for informal learning. This could include implementing mentorship programs, encouraging knowledge-sharing among employees and offering training and development resources to help workers adapt to AI-driven changes. Additionally, the findings highlight the importance of promoting employee learning orientation, which can enhance the effectiveness of such initiatives. ORIGINALITY/VALUE: The study contributes to the existing literature by addressing a relatively unexplored area - the impact of AI awareness on healthcare workers' well-being. While previous research has focused on the potential job displacement effects of AI, this study takes a unique perspective by examining how health workers' perceptions of AI integration can shape their informal learning behaviour and, subsequently, their workplace well-being. By drawing on the JD-R model and incorporating employee learning orientation as a moderator, the study offers a novel theoretical framework for understanding the implications of AI adoption in healthcare organizations.

Humans↗
PubMed2026

Syndemics, violence and injury: exploring historical relationships between infectious disease epidemics and violent crime in South Africa.

This paper explores historical and contemporary intersections between mass-mortality epidemics and violent crime in South Africa, focusing on four major epidemics - Spanish Flu, tuberculosis, HIV, and Covid-19. The study integrates epidemiological data and contextual historical information such as crime statistics, archival records, and secondary scholarship to explore whether epidemic-driven mortality crises are associated with subsequent changes in violence and injury profiles. With the possible exception of gendered violence, the study finds little evidence that earlier epidemics directly contributed to rapid or sustained increases in violent crime, despite causing substantial adult mortality and long-term social and economic disruption. A comparison between epidemic and socio-economic profiles strongly suggests that the significant increases in violent crime recorded after the Covid-19 pandemic are highly localised, and may be more strongly related to lockdown responses, including alcohol restrictions, rather than the effects of disease itself.

Humans↗
PubMed2026

A Meta-learning-driven strategy for adulteration detection in sweet potato starch and vermicelli using Raman spectroscopy.

To address the widespread adulteration of sweet potato starch and its vermicelli with cheaper starches and overcome conventional supervised learning's dependency on large labeled datasets, this study developed a few-shot discrimination method integrating Raman spectroscopy with meta-learning. We constructed a meta-learning framework using cassava- and wheat-adulterated sweet potato starch as the source domain for training, with potato-adulterated sweet potato starch and cassava-adulterated sweet potato vermicelli as two target domains for testing. Raman spectra showed high consistency between sweet potato vermicelli and its raw starch, laying the foundation for cross-domain detection. Testing yielded comprehensive classification accuracies of 95.33% and 98.00% for the two target domains, significantly outperforming SVM, RF, and CNN (max. 85.24%). This approach effectively identifies subtle starch variety differences in complex adulteration, providing novel food quality inspection solutions and verifying the feasibility of raw material-to-finished product cross-domain detection.

Ipomoea batatas↗
PubMed2026

Your story, your brand: A career core competency for nurses.

Intentional management of one's professional story, or narrative discipline , is now a core competency and responsibility for nurses at all career stages. Workforce mobility, interdisciplinary collaboration, broadening career opportunities, and the expansion of digital platforms have elevated the importance of how nurses are perceived by colleagues, organizations, and the public. Increasingly, a nurse's professional story and digital footprint influence professional opportunities, career advancement, and even employment decisions.Many companies invest heavily in brand management to build trust and emotional connection with the people they serve. Importantly, narrative discipline also contributes directly to healthy work environments by reinforcing trust, role clarity, respect, and psychological safety. Drawing from leadership practice, emerging research on nurses' social media use, healthy work environment principles, and guidance from national nurse leadership organizations, this article outlines how nurses can align personal, professional, and enterprise identities; use language deliberately; and engage with discipline and integrity. Practical strategies are provided to help nurses move from passive narrative formation to intentional storytelling that supports career development, workforce engagement, organizational trust, and the sustainability of the nursing profession.

Humans↗
PubMed2026

Whole-Genome Deep Learning Predicts Chemotherapy Response in Colorectal Cancer.

Chemotherapy response in colorectal cancer (CRC) exhibits significant heterogeneity, with current clinical predictors failing to capture complex genomic determinants of resistance. We developed a hybrid deep learning framework integrating convolutional neural networks (CNNs) and bidirectional long short-term memory (BiLSTM) networks to analyze whole-genome somatic mutations, evolutionary conservation, chromatin accessibility, and 3D genome architecture in 2,546 TCGA patients. An attention mechanism identified predictive genomic regions. The model achieved an AUC of 0.92 (95% CI: 0.89-0.94) in cross-validation and 0.88 (95% CI: 0.85-0.91) in independent validation, outperforming clinical models (&#x394;AUC = +0.18, p < 0.001). Key predictors included non-coding variants in TP53, KRAS, and PIK3CA regulatory regions. Triple-positive patients (mutations in all 3 regions) had significantly worse progression-free survival (HR = 4.7, p < 0.001). Our framework enables accurate chemotherapy response prediction and reveals novel non-coding resistance mechanisms, advancing precision oncology in CRC.

Humans↗
PubMed2026

Transcranial Photobiomodulation Variables Assessment Battery: Development and Validation.

Transcranial photobiomodulation (tPBM) response variability is partly driven by biophysical characteristics such as skin tone and hair properties that attenuate photon penetration, and by lifestyle factors including sleep quality, alcohol use, and nicotine consumption that disrupt the mitochondrial and vascular pathways on which tPBM acts. To date, no validated self-report tool exists to capture these moderators systematically. To address this gap, the tPBM Variables Assessment Battery was developed and psychometrically evaluated. It integrates adapted versions of established measures (Brief Pittsburgh Sleep Quality Index, E-cigarette Dependence Scale, Hair Scale Assessment PRO, Monk Skin Tone Scale, and Heaviness of Smoking Index), validated wellbeing evaluators (Ryff's Psychological Wellbeing), and custom measures (Hairstyle Classification, Hair Color Classification). Face and content validity met recommended expert thresholds, internal consistency was acceptable across adapted subscales, and criterion validity analyses confirmed meaningful associations between the lifestyle components and PROMIS-10 global health outcomes. The battery is low-burden, digitally deployable, and psychometrically defensible, offering a practical tool for characterizing the variables most likely to moderate tPBM response in home-use studies.

Humans↗