340880 research outputs found
Sort by
Exploring Medical Students' Learning Through Interprofessional Interactions in Clinical Clerkships:A Qualitative Analysis
No full textPurpose Medical students need help navigating clinical environments to find ways to engage in and learn from clinical work. Previous explorations focused on how physicians help students, largely neglecting the potential contributions of other health professionals (OHPs). This study explores how students learn to participate in clinical work through interactions with OHPs. Method Using a constructivist grounded theory approach, researchers conducted 17 semistructured interviews with Harvard Medical School students completing clinical clerkships between 2023 and 2024. Students drew rich pictures of interprofessional interactions, which they described in the interviews. Interview data were iteratively collected and analyzed to generate a conceptual understanding of learning mechanisms and outcomes in interprofessional interactions. The landscapes of practice framework provided a sensitizing model. Results Students described interprofessional interactions as entering unfamiliar territory and sought to make sense of what these interactions could tell them about how to act and interact in clinical environments. To address their initial confusion, students relied on intraprofessional lore - knowledge about OHPs verbally shared by peers and physicians. As students had experiences with OHPs, students engaged in sense-making by interpreting their own and others' reactions and reconciling expectations with experience. Through these interactions, students learned to meaningfully participate by developing competence within the physician role and understanding of the roles, boundaries, and relevant expertise of other professions. This learning could be hampered by the interceding influence of intraprofessional lore or difficulties interpreting reactions of OHPs. Conclusions By interacting with OHPs, students learned to participate in clinical work by clarifying how to effectively accomplish the work of a physician as well as the roles and relevant expertise of OHPs. Educators can extract more learning from these interactions by creating mechanisms for students to reflect with OHPs in clerkships and by attending to how physicians and students talk about other professions
Artificial Intelligence and Network Medicine:Path to Precision Medicine
No full textOver the past two decades, network medicine (NM) has evolved to help define disease mechanisms, identify drug targets, and guide increasingly precise therapies. In recent years, the integration of NM with artificial intelligence (AI), particularly deep learning techniques, has evolved with increasing applications. AI techniques help elucidate complex disease mechanisms and define precise therapies. The depth of useful, mechanistic information implicit in molecular interaction networks and prior deep learning successes provide a rational basis for combining NM and AI in the analyses of large multiomic datasets to enhance the speed, predictive precision, and biological insights of the computational process. In this review, we provide a summary of concepts related to the combined use of AI and NM as a path to precision medicine, illustrating the success of this joint approach to biomedical complexity and its ongoing challenges
Sparse outlier-robust PCA for multi-source data
No full textSparse and outlier-robust principal component analysis (PCA) has been a very active field of research recently. Yet, most existing methods apply PCA to a single data set whereas multi-source data—i.e. multiple related data sets requiring joint analysis—arise across many scientific areas. We introduce a novel PCA methodology that simultaneously (i) selects important features, (ii) allows for the detection of global sparse patterns across multiple data sources as well as local source-specific patterns, and (iii) is resistant to outliers. To this end, we develop a regularization problem with a penalty that accommodates global-local structured sparsity patterns, and where an outlier-robust covariance estimator, namely the ssMRCD, is used as plug-in to permit joint, robust analysis across multiple data sources. We provide an efficient implementation of our proposal via the alternating direction method of multipliers and illustrate its practical advantages in simulations and in applications
When less is more:resource constraints and radical innovation in family firms and non-family firms
No full textWhile radical innovation is crucial for long-term organizational success, resource constraints often challenge endeavors toward novel ideas, products, and services. Although there is increasing evidence of the positive impact of resource constraints on radical innovation performance, much still needs to be uncovered regarding the conditions that facilitate this positive impact. Drawing on the recombinative innovation perspective, we explicate the positive impact of knowledge and financial constraints on radical innovation. Moreover, we identify firm type-specifically the distinction between family and non-family firms-as a crucial organizational contingency that sheds more light on the focal relationship. Using data from a broad sample of Belgian firms, we find support for our hypothesis that financial constraints can spur a higher likelihood of introducing radical innovation. Moreover, family firms can better transform knowledge constraints into radical innovation, whereas non-family firms are better at generating radical innovation from financial constraints. By considering the impact of organizational characteristics on firms' ability to innovate from specific constraints radically, we deliver more detailed results on the link between resource constraints and radical innovation
The role of co-benefits in motivating climate change mitigation - Experimental evidence
No full textWe study the role of co-benefits - positive effects of climate change mitigation projects in addition to CO2 reduction - in motivating individuals to donate to such projects. In two artefactual field experiments conducted with large population samples (n = 2400 in total), we test how the existence and specific nature of co-benefits affect donations. In both experiments, we find that co-benefits have a positive impact on participants' willingness to donate. Moreover, our second experiment shows that contributions respond to the nature of co-benefits, and these responses seem to be driven by individuals' preferences for specific types of co-benefits. We further observe that co-benefits also increase donations when making carbon footprints and thus individual responsibility for environmental externalities more salient. In sum, our study provides a comprehensive picture of the potential of co-benefits for increasing donations to climate change mitigation projects and has several implications for the provision of co-benefits information in practice
Preliminary efficacy of an online intervention based on Acceptance and Commitment Therapy for family caregivers of people with dementia:a feasibility study
No full textWith the rising number of dementia cases, supporting family caregivers to maintain their well-being is crucial. Acceptance and Commitment Therapy (ACT) shows promise in promoting psychological flexibility and positive behaviour change. However, it is still developing in caregiving contexts. This study evaluated the preliminary efficacy of a fully online ACT intervention for caregivers of people with dementia. This study employed a pre-post design with two follow-up assessments at 3 and 6 months. A 9-week web-based self-help ACT program, including individual goal setting prior to the intervention, and minimal contact motivational coaching, was provided to 30 family caregivers in the Netherlands. Linear mixed-effect models based on a complete-case analysis showed significant changes in depressive symptoms (mean difference: −3.34, d = −0.78). Significant and sustained improvements were observed in stress (mean difference: −6, d = −1.13) and anxiety (mean difference: −5.55, d = −1.38), both of which were clinically significant. Sense of competence increased (mean difference: 1.1, d = 0.45). ACT-specific measures, including psychological flexibility, engaged living, and inflexibility, also showed significant improvements with medium-to-large effect sizes. This online intervention demonstrated promising preliminary evidence of ACT’s potential efficacy on caregivers’ well-being, warranting further research in larger-scale controlled trials.</p
The influence of School principals’ management on school efficiency:Evidence from Italian schools
No full textThis paper investigates the relationship between school principals’ managerial practices and two key dimensions of school performance: students’ cognitive outcomes and school climate. School performance is assessed using a classical Data Envelopment Analysis (DEA) framework, complemented by both unconditional robust and conditional robust models to evaluate the influence of managerial practices on school efficiency. We introduce a methodological innovation that allows for a nuanced analysis of how contextual variables – specifically, principals’ managerial practices – affect performance, both individually and through their interactions. The analysis is based on 2019 INVALSI data from a nationally representative sample of 8th grade students in Italian schools. The findings show that principals’ practices, as well as the ways in which these practices interact, play a significant role in shaping school efficiency, particularly by promoting a positive and supportive school climate
Numbers Ain't Neutral:A QuantCrit Analysis of the Relationship Among Stereotype Threat, Threat Mitigation, and Identity Safety
No full textPurpose Stereotype threat (fear of fulfilling negative stereotypes about one's group) hinders performance through mechanisms such as overwhelming working memory and forcing conscious attention to normally automated cognitive or physical processes. Efforts to combat stereotype threat may include threat mitigation (reactive responses to identity threats) and identity safety (proactively empowering individuals to be their authentic selves). The authors assessed the relationship among stereotype threat, threat mitigation, identity safety, and participant demographics. Method In this cross-sectional study, all U.S. nephrology fellows were invited to complete a survey after the 2024 national in-training examination. The study was anchored in QuantCrit, a research paradigm that applies critical race theory to quantitative methods, and included 8 items using a 5-point Likert scale. The authors performed confirmatory factor analysis to explore statistical validity for the proposed model. Exploring stereotype threat as the dependent variable, the authors compared non-QuantCrit with QuantCrit analysis. Results Overall, 646 of 962 fellows responded (66.9% response rate). With confirmatory factor analysis, a 3-factor model achieved best fit. Participants endorsed low stereotype threat (mean [SD], 1.47 [0.87]), moderate threat mitigation (mean [SD], 3.02 [1.25]), and high identity safety (mean [SD], 4.34 [0.81]). In non-QuantCrit and QuantCrit regressions, threat mitigation was positively associated with stereotype threat, whereas identity safety was inversely associated with stereotype threat. Non-QuantCrit analysis showed no identity-based differences in stereotype threat. QuantCrit analysis with disaggregated identity categories showed that Southeast Asian and Black fellows and international medical graduates (IMGs) from Asia and the Middle East had higher stereotype threat. Asian and Black fellows who were IMGs had less stereotype threat than their racial counterparts from U.S. allopathic schools. Conclusions Fellows who experienced more identity safety reported less stereotype threat, whereas fellows who experienced more threat mitigation reported more stereotype threat. QuantCrit analysis demonstrated intergroup differences not apparent in non-QuantCrit analysis
