Talent Development in Achievement Domains: A Psychological Framework for Within- and Cross-Domain Research

Achievement in different domains, such as academics, music, or visual arts, plays a central role in all modern societies. Different psychological models aim to describe and explain achievement and its development in different domains. However, there remains a need for a framework that guides empirical research within and across different domains. With the talent-development-in-achievement-domains (TAD) framework, we provide a general talent-development framework applicable to a wide range of achievement domains. The overarching aim of this framework is to support empirical research by focusing on measurable psychological constructs and their meaning at different levels of talent development. Furthermore, the TAD framework can be used for constructing domain-specific talent-development models. With examples for the application of the TAD framework to the domains of mathematics, music, and visual arts, the review provided supports the suitability of the TAD framework for domain-specific model construction and indicates numerous research gaps and open questions that should be addressed in future research

Varicella Zoster Virus-Specific Hyperimmunoglobulin in the Adjuvant Treatment of Immunocompromised Herpes Zoster Patients: A Case Series

Abstract Introduction Immunocompromised patients are at increased risk for herpes zoster (HZ)-associated complications. Despite standard therapy with systemic antiviral drugs and analgesics, complications are frequently encountered, including generalization of lesions or persistent neuropathic pain, so-called post-herpetic neuralgia (PHN). Given the scarcity of literature and awareness of therapeutic options to improve patient outcomes, especially for vulnerable patient groups, here we describe a strategy based on early intensification of treatment with a varicella zoster virus-specific hyperimmunoglobulin (VZV-IgG), which is approved in the adjuvant treatment of HZ. Methods For this case series, we selected four cases of HZ in patients with impaired immunity due to hemato-oncologic disease or immunosuppressive treatment who presented with either existing generalized lesions and/or severe pain or with other risk factors for a complicated HZ course such as PHN. They were considered to be representative examples of different patient profiles eligible for intensification of treatment by the addition of VZV-IgG to virostatic therapy. Case Report All patients showed a rapid response to combined treatment with VZV-IgG and a virostatic agent. In two patients who had generalized lesions, the formation of new lesions ceased 1 day after VZV-IgG infusion. One patient, with mantle cell lymphoma, achieved complete healing of the lesions 9 days after diagnosis of HZ, a rare occurrence compared to similar cases or cohorts. A patient with HZ in the cervical region showed a good response after a single dose of VZV-IgG. None of the patients developed post-zoster-related complications. Combination therapy of a virostatic agent and VZV-IgG was well tolerated in these four cases. Conclusion This case series demonstrates highly satisfactory treatment effectiveness and tolerability for VZV-IgG in the adjuvant treatment of immunocompromised HZ patients and supports early intensification of HZ therapy in patients at high risk of severe disease progression

Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma

Abstract Artificial intelligence (AI) systems have been shown to help dermatologists diagnose melanoma more accurately, however they lack transparency, hindering user acceptance. Explainable AI (XAI) methods can help to increase transparency, yet often lack precise, domain-specific explanations. Moreover, the impact of XAI methods on dermatologists’ decisions has not yet been evaluated. Building upon previous research, we introduce an XAI system that provides precise and domain-specific explanations alongside its differential diagnoses of melanomas and nevi. Through a three-phase study, we assess its impact on dermatologists’ diagnostic accuracy, diagnostic confidence, and trust in the XAI-support. Our results show strong alignment between XAI and dermatologist explanations. We also show that dermatologists’ confidence in their diagnoses, and their trust in the support system significantly increase with XAI compared to conventional AI. This study highlights dermatologists’ willingness to adopt such XAI systems, promoting future use in the clinic