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Whole-Exome Sequencing in a Consanguinity-Enriched South Indian Retinitis Pigmentosa Cohort: Diagnostic Yield and Molecular Spectrum.

PURPOSE: To determine the molecular diagnostic yield, variant spectrum, inheritance architecture, and influence of consanguinity on whole-exome sequencing outcomes in a South Indian retinitis pigmentosa (RP) cohort. DESIGN: Prospective, registry-based cohort study. SUBJECTS: A total of 113 affected participants were enrolled through the Aravind Registry for Inherited Diseases of the Eye, including 109 unrelated probands and 4 affected relatives from already represented families. Primary analyses were restricted to the 109 unrelated probands. METHODS: Whole-exome sequencing was performed using a clinical exome workflow. Variants were interpreted using American College of Medical Genetics and Genomics/Association for Molecular Pathology criteria and cases were categorized as solved, possibly solved, inconclusive, or unsolved using prespecified inheritance-aware rules. MAIN OUTCOME MEASURES: Molecular diagnostic yield, distribution of implicated genes and variant classes, inheritance architecture, and diagnostic yield stratified by consanguinity status. RESULTS: Among the 109 unrelated probands, mean age at testing was 39.3 ± 14.1 years and 58.7% were male. Whole-exome sequencing identified 186 distinct rare variants across 92 inherited retinal disease genes, including 26 pathogenic and 33 likely pathogenic variants. A molecular diagnosis was established in 50 of 109 probands (45.9%), including 42 solved and 8 possibly solved cases; 45 (41.3%) were inconclusive and 14 (12.8%) remained unsolved, including 4 (3.7%) in whom no candidate variant was identified. EYS, USH2A, and ADGRV1 were the most frequently implicated genes. Autosomal recessive (AR) disease predominated (44/50, 88.0%). Consanguineous AR cases were exclusively homozygous (17/17); notably, 68.0% of nonconsanguineous AR cases were also homozygous (P = 0.013). Diagnostic yield was higher in consanguineous probands (51.4% vs. 41.7%), without reaching significance. Recurrent alleles included an established South Asian founder variant (MFSD8 c.1361T>C) and candidate founder alleles in EYS (c.4321C>T) and ADGRV1 (c.14329C>T). CONCLUSIONS: Whole-exome sequencing established a molecular diagnosis in nearly half of this South Indian RP cohort and revealed a predominantly recessive, homozygosity-enriched architecture shaped by consanguinity. These findings define a region-specific variant landscape to support clinical interpretation, genetic counseling, and future trial enrollment in this underrepresented population. FINANCIAL DISCLOSURES: The authors have no proprietary or commercial interest in any materials discussed in this article.

Consanguinity

Healthcare transition readiness in an adolescent and young adult urologic population: The ADHERENT study.

INTRODUCTION: There is a paucity of research regarding transition to adult services within pediatric and adolescent urology. Several recent articles have discussed the barriers in transitioning urologic patients from pediatric to adult health care, but empiric data that may drive intervention are lacking. This study proposes to begin to address this gap in literature and to provide information that may lead to improved understanding of how best to support transition in urologic care. OBJECTIVES: 1) to identify modifiable and non-modifiable factors related to transition readiness as measured by Transition Readiness Assessment Questionnaire (TRAQ) scores in a congenital urologic population and 2) to evaluate the relationships between TRAQ scores (a validated questionnaire measuring transition readiness) and scores measuring anxiety levels related to transition (using an adapted, non-validated questionnaire). STUDY DESIGN: This is a cross-sectional study of adolescent and young adult patients with complex congenital urologic diagnoses. Subjects were electronically administered the validated TRAQ and a study-developed ADHERENT survey, which assesses anxiety and worry surrounding transition. Regression models for the outcomes of the TRAQ and ADHERENT scales were developed to assess multivariable associations with variables of clinical importance. RESULTS: The youngest subgroup (14-17 years of age) compared to the oldest subgroup (21-25 years of age) had significantly lower TRAQ scores [regression estimate = 12.3 (95 % CI: 2.9, 21.7), p = 0.010]. Additionally, single participants versus those in a stable relationship had significantly lower TRAQ scores [estimate = 8.7 (95 % CI: 1.9, 15.4), p = 0.012]. The Spearman correlation coefficient between TRAQ and ADHERENT scores was 0.52 (p = <0.001), indicating a positive, moderate relationship between the two measures, suggesting more readiness correlated with less anxiety. DISCUSSION: This study found that age, higher education, and stable relationship status were associated with higher measures of transition readiness. There was a correlation found between more transition readiness and less anxiety surrounding transition. This finding can be used to inform future research and emphasizes the need for multidisciplinary support throughout the transition process. CONCLUSION: Early discussion of transition of care and education around transition readiness are not the only solution to improving transition success. The second phase of ADHERENT seeks to understand the patient experience and to include adolescents and young adults in shaping effective healthcare transition strategies.

Humans

The Impact of Chatbot Type and Normative Messaging on Chatbot Usage Intention Based on the Health Technology Acceptance Model: Randomized Controlled Trial.

BACKGROUND: Digital health tools, such as health chatbots, may improve access to scalable health support, but adoption remains inconsistent. Existing models do not fully integrate technology acceptance factors with health motivation factors relevant to digital health use. OBJECTIVE: This study proposed and tested the health technology acceptance model and examined whether normative message framing and chatbot type were associated with health motivation, technology acceptance, and intention to use a health chatbot. METHODS: In October 2025, we conducted a 4 &#xd7; 2 between-participants online experiment with 1000 US adults recruited from a nationally representative YouGov panel. Participants were randomized to 1 of 8 conditions varying norm message type (self-oriented, peer-oriented, expert-oriented, or family-oriented) and chatbot type (AI-powered or rule-based) in a cancer prevention and genetic risk information scenario. Outcomes included descriptive norms, injunctive norms, perceived susceptibility, perceived severity, perceived benefits, self-efficacy, perceived ease of use, trust, privacy concerns, and usage intention. Data were analyzed using a multivariate ANOVA with Bonferroni-adjusted post hoc tests and multiple linear regression. RESULTS: Peer-oriented and family-oriented messages produced higher usage intention than expert-oriented messages, and peer-oriented messages also increased descriptive norms, injunctive norms, self-efficacy, and trust. AI-powered chatbots were associated with higher usage intention (P=.02) and greater trust (P=.008) than rule-based chatbots. In regression analyses, the model explained 50.8% of the variance in usage intention. Usage intention was positively associated with descriptive norms (&#x3b2;=0.087; P=.003), injunctive norms (&#x3b2;=0.078; P=.009), perceived susceptibility (&#x3b2;=0.051; P=.03), perceived benefits (&#x3b2;=0.253; P<.001), and trust (&#x3b2;=0.33; P<.001), and negatively associated with perceived severity (&#x3b2;=-0.047; P=.049) and privacy concerns (&#x3b2;=-0.11; P<.001). Perceived ease of use and self-efficacy were not significant predictors. CONCLUSIONS: The health technology acceptance model was a useful framework for explaining the intention to use a health chatbot by combining technology acceptance and health motivation constructs. Both social design features and chatbot design features shaped adoption-related beliefs, with peer-oriented and family-oriented framing and AI-powered chatbots showing particular promise. Trust and privacy concerns remained central determinants of intended use.

Humans

A comparative systematic review of pharmacist education systems and pharmacy service quality in ASEAN-5: Indonesia, Malaysia, Thailand, the Philippines, and Singapore.

BACKGROUND: The global transition toward patient-centered pharmaceutical care has exposed structural disparities in ASEAN pharmacy workforce training and deployment. This review examines four research questions: how pharmacy education systems and accreditation standards differ across Indonesia, Malaysia, Thailand, the Philippines, and Singapore (collectively, the ASEAN-5); the extent to which pre-registration education influences clinical service scope and professional confidence; how education reform and regulatory change have shaped pharmacist clinical roles; and what barriers and enablers exist for regional qualification harmonization. METHODS: A systematic literature review following PRISMA 2020 was conducted. Searches of PubMed/MEDLINE and Scopus, supplemented by grey literature, were completed in May 2026. Of 78 unique records screened, 46 studies published between 2005 and 2026 met inclusion criteria. Quality appraisal used an adapted Mixed Methods Appraisal Tool; synthesis employed narrative thematic analysis. RESULTS: The five countries represent four structurally distinct pharmacy education architectures: Thailand's standardized six-year Doctor of Pharmacy with dual specialization tracks; four-year Bachelor of Pharmacy programmes in Malaysia and the Philippines with institutional variation; Indonesia's clinically underdeveloped system despite rapid expansion; and Singapore's four-year Bachelor of Pharmacy followed by a nationally mandated one-year pre-registration pathway. Evidence links deeper clinical training to broader practice scope, higher confidence, and improved patient outcomes. Reform produced uneven results: Thailand's PharmD transition improved clinical recognition but exposed deployment paradoxes; Singapore achieved the strongest training-to-practice alignment; Indonesia's health insurance reforms were not absorbed by an underprepared workforce; the Philippines lacks a national competency framework. No binding mutual recognition arrangement was identified; divergent qualification structures, incompatible accreditation systems, and an asymmetric evidence base remain the primary barriers. DISCUSSION: These findings indicate that clinical service scope is bounded less by national policy ambition than by the depth and clinical orientation of the pre-registration education that precedes it, and that credentialing reforms which outpace a health system's capacity to absorb new clinical roles, or the reverse, do not by themselves translate into expanded practice. CONCLUSIONS: Pharmacy education across the ASEAN-5 remains nationally distinct and clinically uneven. Clinical service scope is directly bounded by pre-registration education quality. No country has fully closed the education-practice gap. Regional harmonization requires national-level educational reform as a prerequisite.

Humans

Nurse-led attribution remodeling training based on the Neuman systems model to enhance resilience, adaptive coping, and attributional style in women newly diagnosed with breast cancer: A randomized controlled trial.

BACKGROUND: Psychological interventions for patients with breast cancer often overlook the critical role of maladaptive attributional style in shaping their adjustment. Therefore, the need for theory-driven, scalable interventions that target cognitive restructuring, particularly during the vulnerable post-diagnosis period, is clear. OBJECTIVE: To evaluate the effectiveness of a nurse-led attribution remodeling training intervention grounded in the Neuman systems model for improving resilience, adaptive coping, and attributional style among women newly diagnosed with breast cancer. DESIGN: A randomized controlled trial. SETTING: A tertiary general hospital. PARTICIPANTS: A total of 130 eligible women newly diagnosed with breast cancer were recruited between March and November 2024. METHODS: A two-arm parallel-group randomized controlled trial was conducted. Participants were randomly assigned to receive either attribution remodeling training plus routine nursing (n&#xa0;=&#xa0;65) or routine nursing only (n&#xa0;=&#xa0;65). The nurse-led attribution remodeling training intervention, delivered via a blended model of in-person sessions and continued support through the WeChat mobile platform, was designed to systematically reshape maladaptive attributions into more adaptive ones. Resilience (primary indicator), coping strategy (i.e., confrontation, avoidance, resignation), and attributional style (secondary indicators) were assessed at baseline and at 1, 3, and 6&#xa0;months post-baseline. A linear mixed model was used to analyze the effects of group, time, and group-by-time interactions. Effect sizes (Cohen's D) were calculated based on the means and standard deviations. RESULTS: At the 6-month follow-up, the intervention group had better outcomes than the control group in terms of resilience (mean difference: 1.49, 95% confidence interval: 0.37, 2.61), confrontation coping (3.35 [2.33, 4.37]), and adaptive attributional style (4.16 [3.87, 4.45]). Avoidance coping showed a small increase (0.82 [0.22, 1.42]), whereas resignation coping decreased (-1.66 [-2.49, -0.83]). Group effects and group-by-time interactions were statistically significant for all outcomes. Effect sizes at 6&#xa0;months ranged from small for resilience (D&#xa0;=&#xa0;0.28) and avoidance coping (D&#xa0;=&#xa0;0.26) to moderate for confrontation coping (D&#xa0;=&#xa0;0.60) and resignation coping reduction (D&#xa0;=&#xa0;-0.51), and large for attributional style (D&#xa0;=&#xa0;0.94). CONCLUSIONS: Attribution remodeling training is a promising and effective theory-based intervention that can enhance psychological adaptation in women newly diagnosed with breast cancer. By strengthening key defense mechanisms, as conceptualized by the Neuman systems model, the program is effective, scalable, and nurse-deliverable for psycho-oncology care, bridging a critical gap in supportive cancer care and empowering nurses as primary psychological support providers. REGISTRATION: ChiCTR2000031827, registered prospectively on April 11, 2020, www.Chictr.or.cn.

Humans

From fear to empowerment: the&#xa0;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