From the introduction: "There are two variants of fronto-temporal dementia: a behavioral variant (behavioral FTD, bvFTD, Neary et al. (1998)), which causes changes in behavior and personality but leaves syntax, phonology and semantics relatively intact, and a variant that causes impairments in the language processing system (Primary Progessive Aphasia, PPA (Gorno-Tempini et al., 2004). PPA can be subdivided into subtypes fluent (fluent but empty speech, comprehension of word meaning is affected / `semantic dementia') and non-fluent (agrammatism, hesitant or labored speech, word finding problems). Some identify logopenic aphasia as a FTD-variant: fluent aphasia with anomia but intact object recognition and underlying word meaning."
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24-09-2016Purpose: Most speech-language pathologists (SLPs) working with children with developmental language disorder (DLD) do not perform language sample analysis (LSA) on a regular basis, although they do regard LSA as highly informative for goal setting and evaluating grammatical therapy. The primary aim of this study was to identify facilitators, barriers, and needs related to performing LSA by Dutch SLPs working with children with DLD. The secondary aim was to investigate whether a training would change the actual performance of LSA. Method: A focus group with 11 SLPs working in Dutch speech-language pathology practices was conducted. Barriers, facilitators, and needs were identified using thematic analysis and categorized using the theoretical domain framework. To address the barriers, a training was developed using software program CLAN. Changes in barriers and use of LSA were evaluated with a survey sent to participants before, directly after, and 3 months posttraining. Results: The barriers reported in the focus group were SLPs’ lack of knowledge and skills, time investment, negative beliefs about their capabilities, differences in beliefs about their professional role, and no reimbursement from health insurance companies. Posttraining survey results revealed that LSA was not performed more often in daily practice. Using CLAN was not the solution according to participating SLPs. Time investment remained a huge barrier. Conclusions: A training in performing LSA did not resolve the time investment barrier experienced by SLPs. User-friendly software, developed in codesign with SLPs might provide a solution. For the short-term, shorter samples, preferably from narrative tasks, should be considered.
In dit boekje over crowdsourcing worden een aantal relevante aspecten van crowdsourcing behandeld. Allereerst beschrijven we een aantal historische voorbeelden om duidelijk te maken dat crowdsourcing niet ontstaan is als gevolg van de opkomst van internet maar als fenomeen al bestond voor het internettijdperk. Door internet is het echter zonder meer eenvoudiger geworden crowdsourcing te organiseren en een veel grotere groepen deelnemers te betrekken. In de sectie 'Wisdom of the Crowds' gaan we in op de onderliggende principes van crowdsourcing. Crowdsourcing wordt vaak in één adem genoemd met de 'Wisdom of the Crowds', als onderliggend mechanisme hoe en waarom crowdsourcing werkt. We zullen echter concluderen dat de 'Wisdom of the Crowds' slechts één van de drie onderliggende principes van crowdsourcing is. Vervolgens gaan we in op de verschillende verschijningsvormen van crowdsourcing. Na een reflectie op bestaande voorstellen om tot een categorisering te komen van deze verschijningsvormen, presenteren we zeven categorieën op basis van het te onderscheiden doel. Bij de keuze om crowdsourcing in te zetten zal naar de kosten, risico's en baten ervan gekeken moeten worden. In de sectie 'Kosten en baten van crowdsourcing' bekijken we dit aspect voornamelijk vanuit het perspectief van de initiërende organisatie. Maar de kosten en baten voor de deelnemers zullen ook kort beschreven worden om te begrijpen wat hen drijft om aan een crowdsourcingproject mee te doen. In de laatste sectie beantwoorden we de vraag hoe crowdsourcing zo effectief en efficiënt mogelijk is in te zetten door naar een aantal implementatiemodellen te kijken en algemene adviezen te inventariseren. We sluiten af met een reflectie op de beschreven bevindingen.
Developing a framework that integrates Advanced Language Models into the qualitative research process.Qualitative research, vital for understanding complex phenomena, is often limited by labour-intensive data collection, transcription, and analysis processes. This hinders scalability, accessibility, and efficiency in both academic and industry contexts. As a result, insights are often delayed or incomplete, impacting decision-making, policy development, and innovation. The lack of tools to enhance accuracy and reduce human error exacerbates these challenges, particularly for projects requiring large datasets or quick iterations. Addressing these inefficiencies through AI-driven solutions like AIDA can empower researchers, enhance outcomes, and make qualitative research more inclusive, impactful, and efficient.The AIDA project enhances qualitative research by integrating AI technologies to streamline transcription, coding, and analysis processes. This innovation enables researchers to analyse larger datasets with greater efficiency and accuracy, providing faster and more comprehensive insights. By reducing manual effort and human error, AIDA empowers organisations to make informed decisions and implement evidence-based policies more effectively. Its scalability supports diverse societal and industry applications, from healthcare to market research, fostering innovation and addressing complex challenges. Ultimately, AIDA contributes to improving research quality, accessibility, and societal relevance, driving advancements across multiple sectors.
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