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Educators within post-secondary institutions receive input in the form of course evaluations from their students. The aim of receiving student input is to improve the teaching and learning experience for all. There are, however, inherent problems with the current methods of obtaining students' views through course evaluations. In this pilot study, the researchers focused on two problems: universally low response rates of 20% or less of student input in formal course evaluations and the problematic bias associated with anonymous course evaluations. Implementing practices that encourage students to provide course feedback, thus moving away from the term course evaluation was a first step to address these problems. A process was piloted in this study with 16 domestic undergraduate Bachelor of Science students whereby the researchers encouraged reflection, dialogue, and accountability in the new model and compared the differences against the problematic original model of receiving course evaluation input from students. [Articles in this journal were presented at the University of Calgary Conference on Postsecondary Learning and Teaching.]

The paper is based on the concept of political culture, which is particularly important for the maintenance and functioning of a democratic political system and is closely linked with the political literacy of young people. In this paper research focus is on the two dimensions of political culture -- political values and trust. Specifically, the main research question is: what are the determinants of accepting constitutional values and the trust in political institutions of final year secondary school pupils? The paper use the data provided by research on political literacy of final year secondary school pupils. In order to provide answer to the research question the hierarchical multiple regression is used. In the first step, particular socio-demographic variables (sex, education of mother and education of father) were introduced. In the second step, the type of secondary school education was added. The third group of predictors encompassed the level of religiosity, generalized prejudices and authoritarianism. In the final step political knowledge was included. The introduced model provides certain explanation regarding constitutional values, but fails to explain distrust in political institutions. The phenomenon of low trust in political institutions is discussed in paper.

Increasing research focus is placed on how to embed social justice within Education degrees. This paper reports findings from the first two phases of a cohort study completed just before and at the start of the pandemic, which track Scottish Education students' reflections on social justice at one university. We used three focus groups (n = 14) and surveys to analyse students' (n = 45) definitions of social justice. Using Bronfenbrenner's Ecological System's Theory and Saldana's Analytical Coding framework we found that themes around prejudice, culture, policy and emerging professional identity captured participants' reflections as both beginning teachers and students of educational studies. Key to our findings was that fewer reflections of social justice were cited to global than to local contexts. This paper highlights ways in which university educators may conceive of social justice such that it is considered by students in both their immediate and in global contexts.

Systematic reviews and maps are considered a reliable form of research evidence, but often neglect non-English-language literature, which can be a source of important evidence. To understand the barriers that might limit authors' ability or intent to find and include non-English-language literature, we assessed factors that may predict the inclusion of non-English-language literature in ecological systematic reviews and maps, as well as the review authors' perspectives. We assessed systematic reviews and maps published in "Environmental Evidence" (n = 72). We also surveyed authors from each paper (n = 32 responses), gathering information on the barriers to the inclusion of non-English language literature. 44% of the reviewed papers (32/72) excluded non-English literature from their searches and inclusions. Commonly cited reasons included constraints related to resources and time. Regression analysis revealed that reviews with larger author teams, authors from diverse countries, especially those with non-English primary languages, and teams with multilingual capabilities searched in a significantly greater number of non-English languages. Our survey exposed limited language diversity within the review teams and inadequate funding as the principal barriers to incorporating non-English language literature. To improve language inclusion and reduce bias in systematic reviews and maps, our study suggests increasing language diversity within review teams. Combining machine translation with language skills can alleviate the financial and resource burdens of translation. Funding applications could also include translation costs. Additionally, establishing language exchange systems would enable access to information in more languages. Further studies investigating language inclusion in other journals would strengthen these conclusions.

Life course epidemiology is hampered by the absence of large studies with exposures and outcomes measured at different life stages in the same individuals. We describe when the effect of an exposure ( A ) on an outcome ( Y ) in a target population is identifiable in a combined ("synthetic") cohort created by pooling an early-life cohort including measures of A with a late-life cohort including measures of Y . We enumerate causal assumptions needed for unbiased effect estimation in the synthetic cohort and illustrate by simulating target populations under four causal models. From each target population, we randomly sampled early- and late-life cohorts and created a synthetic cohort by matching individuals from the two cohorts based on mediators and confounders. We estimated the effect of A on Y in the synthetic cohort, varying matching variables, the match ratio, and the strength of association between matching variables and A . Finally, we compared bias in the synthetic cohort estimates when matching variables did not d-separate A and Y to the bias expected in the original cohort. When the set of matching variables includes all variables d-connecting exposure and outcome (i.e., variables blocking all backdoor and front-door pathways), the synthetic cohort yields unbiased effect estimates. Even when matching variables did not fully account for confounders, the synthetic cohort estimate was sometimes less biased than comparable estimates in the original cohort. Methods based on merging cohorts may hasten the evaluation of early- and mid-life determinants of late-life health but rely on available measures of both confounders and mediators., Competing Interests: Disclosure: The authors report no conflicts of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Recent advancements in generative artificial intelligence (GAI) have sparked debates and research on its transformative potential in education. This study explored how a specific group of educators partner with GAI tools, particularly ChatGPT, to complement and enhance their teaching. Within an interpretative paradigm, the study used an exploratory case study design to investigate how 13 educators enrolled as students in a structured master's programme at an open distance learning university in South Africa use GAI tools in their teaching. Their posts on a discussion forum were used to collect data. Findings reveal that they actively employ GAI to streamline their teaching practices, specifically to personalized tutors, simplifying English texts and translations, assessments, lesson planning, and critical thinking tasks. The study also highlights the need to understand the limitations and boundaries of GAI, including concerns about accuracy, biases and reliability. Importantly, the absence of institutional guidelines on GAI raises questions about the necessity for clear guidelines and policies to ensure responsible and ethical integration in educational contexts. The paper concludes by emphasizing the transformative potential of GAI and the fact that it will increasingly act as a partner in teaching and influence modern teaching practices. Ultimately, GAI's foothold in education is undeniable, challenging educators and policymakers to navigate its implications while maximizing its potential to support effective teaching.

Purpose: This paper aims to explore how an academic researcher and a practitioner experience scepticism for their qualitative research. Design/methodology/approach: The study applies Olt and Teman's new conceptual phenomenological polyethnography (2019) methodology, a hybrid of phenomenology and duoethnography. Findings: For the researcher-participants, the essence of living with scepticism means feeling a sense of injustice; struggling with the desire for simplicity and quantification; being in a circle of uneasiness; having a survival mechanism; and embracing healthy scepticism. They experience the essence differently and similarly in varied cultural contexts. Through duoethnographic conversations, they acknowledge that while there can be scepticism of their work, it is important to remain sceptical, persistent and curious by challenging traditional concepts. Theoretical and practical advances in artificial intelligence (AI) continue to highlight the need for clarifying qualitative researcher roles in academia and practice. Originality/value: This paper contributes to the debate of qualitative versus quantitative research. Its originality is in exploring scepticism as lived experience, from an academic and practitioner perspective and applying a phenomenological polyethnography approach that blends two different traditional research paradigms.

In this theoretical paper, I bring together work on structural, racial, and affective gaslighting to turn attention to 'affective injustice' as a distinct kind of injustice suffered by victims of racial gaslighting in educational settings. Under this conceptual framework, it is possible to explore how education spaces facilitate racial gaslighting as a form of affective injustice -- from the intentional prejudices of individuals (students and educators) to the unconscious biases and insidious norms that allow the production of racialized practices and pathologize students and educators of color for their resistance against white supremacy. I argue that a social and political theory of racial gaslighting in education offers an opportunity to identify and analyze how gaslighting mobilizes racialized stereotypes and structural inequalities to perpetuate affective injustice against marginalized educators and students. The paper concludes with a discussion of the theoretical and pedagogical implications of examining racial gaslighting in education.

This paper identifies the need for a pedagogical re-orientation in UK higher education to prepare graduates to overcome wicked problems. In addition to key knowledge sets, graduates need attributes of critical self-reflection, risk-awareness and management, collaboration, creativity, agility, reflexivity - enabling the ability to manage the unknown. In response, researchers have acknowledged the importance of pedagogies that are risk-oriented, creative, and reflective to remedy modernist banking methods. This paper acknowledges that while such pedagogies are underutilised, an antagonistic dichotomy between modernist banking methods (bad) and enquiry and risk-oriented approaches (good) is unhelpful as both approaches are necessary. This paper develops a metamodern framework to guide pedagogic practices to facilitate a disposition among learning strategists and practitioners which embraces oscillation between banking and radical pedagogic approaches. In turn this enables the development of student sensibilities, empowering them to challenge the growing wickedness with which they must do battle.

I am an example of a transformed higher education administrator. In this essay, I describe how my journey to an education doctorate impacts my work as a scholar-practitioner in higher education. The CANDEL program challenged what I thought I understood about the status quo in higher education with respect to race, socioeconomic impacts, meritocracy, grit, and assumptions we make about students. The coursework and cohort model confronted my own biases and were foundational to my dissertation questions. Conducting my research on university leadership at my home institution gave me an opportunity to develop a shared equity leadership approach to solving complex problems. Equity-focused work in higher education is a long-game, ongoing, and essential to addressing the challenges facing our institutions. Without this, inequities experienced by faculty, staff and students will persist. The education doctorate and its scholar-practitioners are important drivers in shifting the American educational landscape.

Predictive student models are increasingly used in learning environments due to their ability to enhance educational outcomes and support stakeholders in making informed decisions. However, predictive models can be biased and produce unfair outcomes, leading to potential discrimination against certain individuals and harmful long-term implications. This has prompted research on fairness metrics meant to capture and quantify such biases. Nonetheless, current metrics primarily focus on predictive performance comparisons between groups, without considering the behavior of the models or the severity of the biases in the outcomes. To address this gap, we proposed a novel metric in a previous work (Verger et al., 2023) named "Model Absolute Density Distance" (MADD), measuring algorithmic unfairness as the difference of the probability distributions of the model's outcomes. In this paper, we extended our previous work with two major additions. Firstly, we provided theoretical and practical considerations on a hyperparameter of MADD, named "bandwidth," useful for optimal measurement of fairness with this metric. Secondly, we demonstrated how MADD can be used not only to measure unfairness but also to mitigate it through postprocessing of the model's outcomes while preserving its accuracy. We experimented with our approach on the same task of predicting student success in online courses as our previous work, and obtained successful results. To facilitate replication and future usages of MADD in different contexts, we developed an open-source Python package called maddlib (https://pypi.org/project/maddlib/). Altogether, our work contributes to advancing the research on fair student models in education.

In Australia, the Teaching Performance Assessment (TPA) is a relatively new, mandatory hurdle which must be completed just prior to the graduation stage of initial teacher education (ITE) programmes. This high-stakes task is one of a growing number of requirements to come out of the standards and accountability regime as outlined in the Australian Institute for Teaching and School Leadership (AITSL) document for accreditation for ITE programmes. We delve into the public commentary about the broader commission of preservice and graduate teacher quality in general and the TPA in particular. We draw on Bernstein's pedagogic identities and deductively apply this theory to explore this phenomenon. We use a data set of publicly available legacy media and social media tweets made over a ten-month period from August 2019 to May 2020 to reveal the focus, inherent bias and pedagogic identities promoted by these public discourses. The paper concludes with discussion about the implications of these drivers on the public perception of quality in ITE and on the status of teaching more broadly.

Children's books play a central role in today's classrooms. Educators can use children's literature to promote children's social and cultural understandings and critical thinking skills. This is particularly important when extending children's knowledge and understandings of themselves, their identity and those who may differ culturally, socially or historically, thus supporting diversity and inclusion. Further, when diversity is considered, valued, and supported through Culturally Responsive Pedagogy (CRP), outcomes for children from underrepresented backgrounds improve. This paper reports on a study conducted in four early learning settings in Western Australia investigating educators' practices when sharing diverse literature with young children. This study found in the majority of book sharing in these centres the cultures, backgrounds, life experiences and funds of knowledge of children from underrepresented backgrounds were invisible. Further, educators' practices were bereft of CRP and likely to demean and confuse those from underrepresented backgrounds and increase all children's misconceptions of others.

In this paper, we explored how political knowledge related to generalised prejudice, defined as the common variance of three highly correlated specific prejudice concerning ethnicity, gender and sexual orientation. We aligned our hypotheses with the Cognitive Ability and Style to Evaluation (CASE) model, which postulates the mechanism underlying the relationship between individual-level cognitive variables and intergroup outcomes. As knowledge in its many forms correlates with and serves as a proxy of cognitive abilities, we hypothesised that political knowledge, when considered a precursor of prejudice, can be expected to act similarly to cognitive variables within the CASE model. We performed an empirical test of the hypothesised relationships on a nationally representative sample of Croatian students in their final year of secondary education (aged 17-19). As expected, there was a significant negative association between political knowledge and generalised prejudice, both direct and indirect via right-wing authoritarianism. Youth with higher political knowledge had significantly lower levels of generalised prejudice. In addition, while there were differences in the overall levels of political knowledge, right-wing authoritarianism and generalised prejudice between students attending different secondary education programmes, the pattern of relationships between these concepts was found to be stable across educational settings.

Perioperative nurses must provide culturally competent care to all surgical patients, and understanding gender identity and gender diversity may be the first step to creating an inclusive perioperative practice for transgender and gender diverse patients. In the nurse--patient relationship, limited exposure to and knowledge of diverse populations may negatively affect the health of this important demographic. When nurses are unaware of how care can be affected by explicit (conscious) or implicit (unconscious) bias, they may use transphobic stereotyping behaviours or act with microaggressions, like using excessive protective attire. Such care may invalidate gender identity and impede trust. In contrast, nurses practising gender-affirming care validate the patient's gender identity and life experiences, which supports autonomy and creates trust. The aim of this paper is to provide perioperative nurses with a deeper understanding of factors that may affect gender diverse patient's perioperative outcomes. In addition, understanding the social determinants of health affecting this demographic may result in better health outcomes. As such, the holistic care of the transgender and gender diverse patient is the optimal goal, with clinicians employing a non-judgemental, sensitive and compassionate attitude. [ABSTRACT FROM AUTHOR]

A dramatic shift in the global food system is occurring with the rapid growth of ultra-processed foods (UPFs) consumption, which poses potentially serious health risks. Systematic review (SR) method has been used to summarise the association between UPF consumption and multiple health outcomes; however, a suboptimal-quality SR may mislead the decision-making in clinical practices and health policies. Therefore, a methodological review was conducted to identify the areas that can be improved regarding the risk of bias and reporting quality of relevant SRs. Systematic searches to collect SRs with meta-analyses of UPFs were performed using four databases from their inception to April 14, 2023. The risk of bias and reporting quality were evaluated using ROBIS and PRISMA 2020, respectively. The key characteristics of the included SRs were summarised descriptively. Excel 2019 and R 4.2.3 were used to analyse the data and draw graphs. Finally, 16 relevant SRs written in English and published between 2020 and 2023 in 12 academic journals were included. Only one SR was rated as low risk of bias, and the others were rated as higher risk of bias mainly because the risk of bias in the original studies was not explicitly addressed when synthesising the evidence. The reporting was required to be advanced significantly, involving amendments of registration and protocol, data and analytic code statement, and lists of excluded studies with justifications. The reviews' results could improve the quality, strengthen future relevant SRs' robustness, and further underpin the evidence base for supporting clinical decisions and health policies., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

In clustered randomized controlled trials (RCTs), sample recruitment is often conducted after cluster randomization. This timing can lead to recruitment bias if access to the intervention affects the composition of study-eligible cluster entrants and study consenters. This article develops a potential outcomes framework in such settings that yields a causal estimand that pertains to the always-recruited in either research condition. A consistent inverse probability weighting (IPW) estimator is developed using data on recruits only, and a generalized estimating equations approach is used to obtain robust clustered SE estimators that adjust for estimation error in the IPW weights. A simple data collection strategy is discussed to improve the predictive accuracy of the logit propensity score models. Simulations show that the IPW estimator achieves nominal confidence interval coverage under the assumed identification conditions. An empirical application demonstrates the methods using data from an RCT testing the effects of a behavioral health intervention in schools. An R program for estimation is available for download., (© 2023 John Wiley & Sons Ltd.)

A critical debate has blossomed within the field of research policy, science and technology studies, and philosophy of science regarding the possible benefits and limitations of allocating extramural grants using a lottery system. The most common view among those supporting the lottery idea is that some form of modified lottery is acceptable, if properly combined with peer review. This means that partial randomization can be applied only after experts have screened the pursuit-worthiness of all submitted proposals and sorted out those of lowest quality. In the present paper, I will argue against the use of partial lotteries or partial randomization and instead promote use of a "pure lottery" in combination with a radical increase in block funding. The main reason for holding this position is that a partial lottery cannot solve the problems inherent in the current funding system, which is based on grant competitions and peer review. A partial lottery cannot decrease the enormous time-waste, reduce the uneven distribution of time between researchers, neutralize expert biases or mitigate academic power asymmetries. Instead, we need a stronger focus on improving general time management in academia by implementing a more holistic model for organizing research opportunities in the future.

Implicit prejudice can be simply understood as any negative feelings or beliefs people hold towards a particular outgroup without being aware of it. One such form is microaggression, which can be defined as everyday verbal or nonverbal subtle, unconscious putdowns, slights, or negative remarks towards members of an outgroup. One of the most common and harmful forms is gender-based microaggression. Gender microaggression is defined as subtle, unconscious, everyday putdowns, slights, remarks, or insults, whether intentional or unintentional, directed at a particular gender, notably women. Despite a plethora of literature and research on gender microaggression, the focus has predominantly been on understanding microaggressions faced by women in various domains, largely neglecting the experiences of men as victims of microaggression. One such overlooked experience is that of Afghan male students studying in universities in Delhi. Each year, thousands of students from Afghanistan travel to Delhi to pursue higher education, often unaware of the prejudices they may encounter due to associations with terms like 'terrorism' or 'terrorist.' Therefore, this paper aims to understand and study the microaggression faced by Afghan male students by employing the Gender Implicit Association Test on a sample of 103 Indian students studying in universities in Delhi, selected using a snowball sampling technique. This study adapts and modifies the Weapon-based Implicit Association Test. The goal is to uncover the implicit biases of Indian students towards Afghan male students by examining the association (reaction time) between images of weapons and harmless objects, in conjunction with adjectives related to Afghan males and Afghan females. In other words, words or images that are congruent in our minds should result in shorter reaction times and fewer errors compared to words and images that are incongruent. The results indicate that Indian students were quicker in associating weapon images with Afghan male adjectives (D = -0.64) compared to Afghan female adjectives (D = 0.89).

Influence from bias is unavoidable in clinical decision-making, and mental health assessment seems particularly vulnerable. Individuals with intellectual disabilities have increased risk of developing co-occurring mental disorder. Due to the inherent difficulties associated with intellectual disabilities, assessment of mental health in this population often relies on a different set of strategies, and it is unclear how these may affect risk of bias. In this theoretical paper, we apply recent conceptualisations of bias in clinical decision-making to the specific challenges and strategies in mental health assessment in intellectual disabilities. We suggest that clinical decision-making in these assessments is particularly vulnerable to bias, including sources of bias present in mental health assessment in the general population, as well as potential sources of bias which may be specific to assessments in this population. It follows that to manage potential bias, triangulating information from multi-informant, multi-method, interdisciplinary assessment strategies is likely to be necessary.

The programme outcomes are broad statements of knowledge, skills, and competencies that the students should be able to demonstrate upon graduation from a programme, while the Educational Taxonomy classifies learning objectives into different domains. The precise mapping of a course outcomes to the programme outcome and the educational taxonomy (Cognitive, Psychomotor and Affective) level is crucial to ensure Constructive Alignment at the fundamental level of a course and to ensure meaningful outcome measurements. Unfortunately, this effort is often subject to bias and human error while the use of information technologies as a mediator in this area remains unexplored. This research paper proposes an automatic learning-based advisory system for engineering curriculum to ensure constructive alignment with programme outcomes and educational taxonomy. We demonstrated the use of natural language processing and machine learning techniques to mitigate human error and bias that is often present in such classification tasks. Textual/semantic embeddings, including Term Frequency-Inverse Document Frequency (TF-IDF), Universal Sentence Encoder (USE), and Word2Vec (W2V), machine learning models (Random Forest, Support Vector Machine, Logistic Regression, and Light Gradient Boosting Machine), and their corresponding techniques for optimizing the training process are extensively investigated. In terms of accuracy, we obtained an encouraging result of 78.83%, and 78.71% for TF-IDF with Random Forest, and USE with Support Vector Machine classifier, respectively. We transformed our work into a web-based solution named the Course Outcomes Diagnostic Tool, embedded in the faculty education web platform, Edu Centre that is ubiquitously adopted by the members in the Faculty of Engineering and Technology, Tunku Abdul Rahman University of Management and Technology. The proposed solution has demonstrated great potential in reducing subjectivity, ambiguity, and human error, thereby improving the constructive alignment at the root level of course design to ensures teaching-learning activities are aligned with regulatory body expectations.

Social institutions function not only by reproducing specific practices but also by reproducing discourses endowing such practices with meaning. The latter in turn is related to the development of the identities or subjectivities of those who live and thrive within such institutions. Meaning and subjectivity are therefore significant sociological categories involved in the functioning of complex social phenomena such as that of mathematical instruction. The present paper provides a discursive analysis centered on these categories of the influential OECD's PISA mathematics frameworks. As we shall see, meaning as articulated by the OECD primarily stresses the utilitarian value of mathematics to individuals and to society at large. Furthermore, molding students' subjectivities towards endorsing such articulation of meaning is emphasized as an educational objective, either explicitly or implicitly, as connected to the OECD's definition of mathematical literacy. Therefore, the OECD's discourses do not only serve to reproduce the type of mathematical instruction implied in the organization's services concerning education, but also concomitantly provide a potentially most effective educational technology through which the demand of these very services may be reproduced.

The emergence of ChatGPT, a Generative AI program, has sparked discussions about its teaching and learning value, and concerns about academic integrity in higher education (HE). An extant review of the literature indicates that a scarcity of research exists on GenAI, specifically a synthesis of the official views, guidelines and articles of top-ranked universities on the use, limitations, challenges, and opportunities brought by ChatGPT in the early phase when ChatGPT was released in 2022 until early May 2023, which can offer insights into the concerns and recommendations for educators. Using the corpus assisted discourse analysis approach, this study identified the key themes and emotions elicited by evaluations of the ChatGPT situation from a self-built corpus containing 151 articles from 47 top-ranked U.S. universities and 34 U.K. ones. Our findings indicated three prominent themes discussed on official websites, including ChatGPT as a text and content generator, use of ChatGPT in teaching and learning, and potential implications and opportunities of using ChatGPT in HE. Further examination revealed that bias, concern, worry, threat, fear, and trust were the prevailing emotions relating to ChatGPT. Illustrated with examples collected from our corpus, this paper offers an in-depth discussion of universities' first responses to the use of ChatGPT. The insights gained have some pedagogical implications for academics, researchers and educators and may inform policy and practice in HE on the use of GenAI.

In this paper we conduct a poststructural discourse analysis inspired by Carol Bacchi's 'What's the problem represented to be?' (WRP) approach. We explore what kinds of problems are formulated in preschool educational policy on multilingualism, and what underlying assumptions underlie the dominant discourse on language proficiency in Sweden. Serving as a case to discuss how racism, ableism and childism intersect with linguicism, we examine the importance of shifting from a 'children's (special) needs' discourse to a 'children's (language) rights' discourse through a social justice education framework. We draw upon Elisabeth Young-Bruehl's understanding of childism, which refers to prejudice and discrimination against children based on beliefs about their inferiority to adults. The right to and rights in education are contingent upon linguistic rights, upon students learning to use their first language, whether that be minority, indigenous or sign language.

The last decade has seen a rise in big data approaches, including in the humanities, whereby large quantities of data are collected and analysed. In this paper, we discuss long-form audio recordings that result from individuals wearing a recording device for many hours. Linguists, psychologists and anthropologists can use them, for example, to study infants' or adults' linguistic behaviour. In the past, recorded individuals and communities have resided in high-income countries (HICs) almost exclusively. Recognising the need for better representation of all cultures and linguistic experiences, researchers have more recently started to collect long-form audio recordings in low- and middle-income countries (LMICs). We aim to help researchers to collect, analyse and use these recordings ethically. To do so, we identify four main ethical challenges linked to research that relies on long-form recordings in LMICs. We provide recommendations to overcome these challenges. These considerations should be useful to researchers employing other big data techniques collected via wearables.

Primary care health checks, screenings and GP consultations are often the gateway for people with intellectual disabilities to access their physical and mental healthcare. For a population who experience greater levels of health difficulties alongside significant health inequality, improving care quality and access is of major importance. This meta-ethnographic, qualitative review aims to explore people with intellectual disabilities experiences of health checks, screenings and GP visits, while assessing the quality of the current literature and synthesising findings to consider clinical and research recommendations based on third order constructs. A systematic search identified 20 studies that met inclusion criteria. Quality assessment of each paper was conducted. Meta-ethnography methods were used to analyse and synthesis findings. One overarching concept was identified: Include Me, along with seven core concepts; Empowerment and Disempowerment, Communication and Interpersonal Factors, Access and Adaptations and Biased Narratives and Shifting Perspectives. Implications for practice and future direction are discussed.

This study investigates how the perceptions of graduate students within a doctoral program in a midsized higher education institution in Southwest Florida evolved over a semester regarding multicultural education and impacted their careers and professional lives. A qualitative case study method was utilized with multiple data sources collected, including interviews, students' written papers, students' presentations, as well as online discussions and assignments that aimed to prepare educational leaders within culturally diverse topics while challenging and impacting their perceptions about diversity, race, cultural, and multicultural education experiences. The findings were that post-doctoral coursework in the area of multicultural education produced three significant themes: (1) false understanding of what multicultural education encompassed, (2) increased awareness of self-biases, lack of resources and training, and (3) finally, a feeling of helplessness where participants want to see transformation but are unable to affect change.

In this paper, I start from a posthumanist understanding of subjectivity to stress how our ways of relating do not follow from previously formed intentions but emerge in assemblages. The fact that we hold certain theoretical ascriptions does not assure that we will relate in ways that are consistent with them. We might intend to embrace diffractive, decentring and performative perspectives, and effectively do so at a content level. However, we might unwittingly reproduce representational, dichotomous, centring and identitarian ways of relating to ourselves, others, our work and so on. These ways of relating are often unacknowledged. I offer my concept of "performative meta-reflexivity" to interrogate which ways of relating are implicitly operating and to think about what they are producing. I suggest that this practice can be helpful to become response-able for the ways of relating that we find ourselves engaged in and what they generate.

The article examined the effectiveness of using summative evaluation in developing a deep understanding and critical thinking skills among secondary school students. Preparing questions which contain an explanation of concepts in the question paper helps the students to develop a deep understanding and critical thinking skills while answering. The answers of the students were analyzed both quantitatively and qualitatively. The researchers identified five themes based on Bloom's theory of cognitive taxonomy to explore the critical thinking skills of the respondents. There were five components: comprehension, application, analysis, synthesis, and evaluation. Content analysis indicated that the above method limits the confirmation bias. A comparison of answers to three tests in history showed a significant difference (p < 0.01) between the control group (N = 151) and experimental group students (N = 129). Adding positive or negative content in the description of concepts in the essay question influences the response.

Purpose: The negative cultural bias vis-à-vis international business and cross-cultural management has been duly acknowledged, necessitating recommendations towards investigating its positive effects. Methodologically, quantitative research clearly predominates, and there have been calls for alternative approaches. Thus, this conceptual paper addresses the research gap (methodological and thematic) by investigating if multicultural teams can be an essential part of the global workforce and whether positive effects exist regarding dynamic capabilities, learning and knowledge transfer. Design/methodology/approach: The underlying ethnographic research design enabled exploring within the embedded single case study from an emic perspective, including qualitative observation and semi-structured expert interviews, and provided detailed insights into the company's multicultural work environment. Findings: The results reveal that applying a qualitative design allowed the needed exploration and show that multicultural, geographically dispersed teams are positively experienced and considered necessary in today's globalised world. They are likely to increase in the future. Moreover, dynamic capabilities (multicultural competencies) are indispensable for multicultural teamwork. Regarding learning opportunities, different viewpoints for discussion and the ability to reflect on these offer valuable insights. In line with theory, multiculturality is considered a "two-edged sword", providing simultaneous benefits and challenges. Contrary to the theory, even highly important information transfers can occur virtually, although occasional physical contact is essential for trust building. Originality/value: The multinational family business offers a unique example of a positive relationship between multiculturalism and organisational excellence and demonstrates how the application of a qualitative methodology can support theory building by delivering a revised model of dynamic capabilities in multicultural environments with geographical dispersion.

Background: Medical text, as part of an electronic health record, is an essential information source in healthcare. Although natural language processing (NLP) techniques for medical text are developing fast, successful transfer into clinical practice has been rare. Especially the hospital domain offers great potential while facing several challenges including many documents per patient, multiple departments and complex interrelated processes. Methods: In this work, we survey relevant literature to identify and classify approaches which exploit NLP in the clinical context. Our contribution involves a systematic mapping of related research onto a prototypical patient journey in the hospital, along which medical documents are created, processed and consumed by hospital staff and patients themselves. Specifically, we reviewed which dataset types, dataset languages, model architectures and tasks are researched in current clinical NLP research. Additionally, we extract and analyze major obstacles during development and implementation. We discuss options to address them and argue for a focus on bias mitigation and model explainability. Results: While a patient's hospital journey produces a significant amount of structured and unstructured documents, certain steps and documents receive more research attention than others. Diagnosis, Admission and Discharge are clinical patient steps that are researched often across the surveyed paper. In contrast, our findings reveal significant under-researched areas such as Treatment, Billing, After Care, and Smart Home. Leveraging NLP in these stages can greatly enhance clinical decision-making and patient outcomes. Additionally, clinical NLP models are mostly based on radiology reports, discharge letters and admission notes, even though we have shown that many other documents are produced throughout the patient journey. There is a significant opportunity in analyzing a wider range of medical documents produced throughout the patient journey to improve the applicability and impact of NLP in healthcare. Conclusions: Our findings suggest that there is a significant opportunity to leverage NLP approaches to advance clinical decision-making systems, as there remains a considerable understudied potential for the analysis of patient journey data. [ABSTRACT FROM AUTHOR]

ISO 15189 requires laboratories to estimate the uncertainty of their quantitative measurements and to maintain them within relevant performance specifications. Furthermore, it refers to ISO TS 20914 for instructions on how to estimate the uncertainty and what to take into consideration when communicating uncertainty of measurement with requesting clinicians. These instructions include the responsibility of laboratories to verify that bias is not larger than medically significant. If estimated to be larger than acceptable, such bias first needs to be eliminated or (temporarily) corrected for. In the latter case, the uncertainty of such correction becomes part of the estimation of the total measurement uncertainty. If small enough to be acceptable, bias becomes part of the long term within laboratory random variation. Sources of possible bias are (not limited to) changes in reagent or calibrator lot variation or calibration itself. In this paper we clarify how the rationale and mathematics from an EFLM WG ISO/A position paper on allowable between reagent lot variation can be applied to calculate whether bias can be accepted to become part of long-term imprecision. The central point of this rationale is to prevent the risk that requesting clinicians confuse changes in bias with changes in the steady state of their patients. [ABSTRACT FROM AUTHOR]

Aim: This paper investigates the conditions for inclusive design of regenerative medicine interventions from a bioethical perspective, taking regenerative valve implants as a showcase. Methods: A value hierarchy is construed to translate the value of justice into norms and design requirements for inclusive design of regenerative valve implants. Results: Three norms are proposed and translated into design requirements: regenerative valve implants should be designed to promote equal opportunity to good health for all potential users; equal respect for all potential users should be shown; and the implants should be designed to be accessible to everyone in need. Conclusion: The norms and design requirements help to design regenerative valve implants that are appropriate, respectful and available for everyone in need. Plain Language Summary Scientists in the field of regenerative medicine are developing a new type of heart valve implant. After implantation, the synthetic implant slowly breaks down and is replaced by a new living heart valve. These so-called regenerative implants promise a complete cure. However, they also raise ethical questions. For example, questions related to justice and inclusion. In this paper, we explore how regenerative implants can be designed to be inclusive, meaning suitable, respectful and available for everyone. We argue that the design of regenerative implants should be adapted to relevant differences between users. The implants should be affordable in the short and long term. The implants should be suitable for use worldwide. The implants should be designed by teams of diverse age, gender and ethnicity. Users should be engaged in the design. And the communication about the implants to researchers and users should be inclusive. Overall, this paper provides ethical guidance to researchers and clinicians developing regenerative implants. Article highlights Health research and care should be inclusive to address inequities in health. Inclusion also deserves attention within the rapidly evolving field of regenerative medicine. However, what inclusion means and what inclusive design should entail in the context of regenerative medicine is not clear. This paper investigates the conditions for inclusive design of regenerative medicine interventions, taking regenerative valve implants (i.e., in situ tissue-engineered heart valves) as a showcase. The aim of inclusive design relates to the value of justice. Justice is concerned with recognition (claims about equal respect for marginalized groups and undervalued social identities) and redistribution (the equitable distribution of goods and resources). A values hierarchy is a deliberative tool to translate a value into norms and design requirements in the context of technology design. The value of justice can be translated into three norms: regenerative valve implants should be designed to promote equal opportunity to good health for all potential users; in the design process, equal respect for all potential users should be shown; and the implants should be designed to be accessible to everyone in need. Based on these norms, the following design requirements can be formulated: regenerative valve implants should be designed to account for relevant user differences, be affordable and cost-effective and be suitable for global distribution, and the design process should involve diverse design teams, engage users and use inclusive communication. Together, the norms and design requirements shape the conditions for inclusive design of regenerative valve implants. This paper aids the design of implants that are appropriate, respectful and available for everyone in need. More generally, by exemplifying an ethically proactive approach to the design of regenerative medicine technology, it contributes to responsible development of regenerative medicine interventions. [ABSTRACT FROM AUTHOR]

Integrating artificial intelligence (AI) systems into administrative procedures can revolutionize the way processes are conducted and fundamentally change established forms of action and organization in administrative law. However, implementing AI in administrative procedures requires a comprehensive evaluation of the capabilities and limitations of different systems, including considerations of transparency and data availability. Data are a crucial factor in the operation of AI systems and the validity of their predictions. It is essential to ensure that the data used to train AI algorithms are extensive, representative, and free of bias. Transparency is also an important aspect establishing trust and reliability in AI systems, particularly regarding the potential for transparent representation in rule-based and machine-learning AI systems. This paper examines the potential and challenges that arise from integrating AI into administrative procedures. In addition, the paper offers a nuanced perspective on current developments in artificial intelligence and provides a conceptual framework for its potential applications in administrative procedures. Beyond this, the paper highlights essential framework conditions that require continuous monitoring to ensure optimal results in practice. [ABSTRACT FROM AUTHOR]

Generative Artificial Intelligence (AI) systems, like ChatGPT, have the potential to perpetuate and amplify cultural biases embedded in their training data, which are predominantly produced by dominant cultural groups. This paper explores the philosophical and technical challenges of detecting and mitigating cultural bias in generative AI, drawing on Plato's Allegory of the Cave to frame the issue as a problem of limited and distorted representation. We propose a multifaceted approach combining technical interventions, such as data diversification and culturally aware model constraints, with a deeper engagement with the cultural and philosophical dimensions of the problem. Drawing on theories of extended cognition and situated knowledge, we argue that mitigating AI biases requires a reflexive interrogation of the cultural contexts of AI development and a commitment to empowering marginalized voices and perspectives. We claim that controlling cultural bias in generative AI is inseparable from the larger project of promoting equity, diversity, and inclusion in AI development and governance. By bridging philosophical reflection with technical innovation, this paper contributes to the growing discourse on responsible and inclusive AI, offering a roadmap for detecting and mitigating cultural biases while grappling with the profound cultural implications of these powerful technologies. [ABSTRACT FROM AUTHOR]

Machine learning (ML) has become increasingly prevalent in various domains. However, ML algorithms sometimes give unfair outcomes and discrimination against certain groups. Thereby, bias occurs when our results produce a decision that is systematically incorrect. At various phases of the ML pipeline, such as data collection, pre-processing, model selection, and evaluation, these biases appear. Bias reduction methods for ML have been suggested using a variety of techniques. By changing the data or the model itself, adding more fairness constraints, or both, these methods try to lessen bias. The best technique relies on the particular context and application because each technique has advantages and disadvantages. Therefore, in this paper, we present a comprehensive survey of bias mitigation techniques in machine learning (ML) with a focus on in-depth exploration of methods, including adversarial training. We examine the diverse types of bias that can afflict ML systems, elucidate current research trends, and address future challenges. Our discussion encompasses a detailed analysis of pre-processing, in-processing, and post-processing methods, including their respective pros and cons. Moreover, we go beyond qualitative assessments by quantifying the strategies for bias reduction and providing empirical evidence and performance metrics. This paper serves as an invaluable resource for researchers, practitioners, and policymakers seeking to navigate the intricate landscape of bias in ML, offering both a profound understanding of the issue and actionable insights for responsible and effective bias mitigation. [ABSTRACT FROM AUTHOR]

Digital health technologies can generate data that can be used to train artificial intelligence (AI) algorithms, which have been particularly transformative in cardiovascular health-care delivery. However, digital and health-care data repositories that are used to train AI algorithms can introduce bias when data are homogeneous and health-care processes are inequitable. AI bias can also be introduced during algorithm development, testing, implementation, and post-implementation processes. The consequences of AI algorithmic bias can be considerable, including missed diagnoses, misclassification of disease, incorrect risk prediction, and inappropriate treatment recommendations. This bias can disproportionately affect marginalised demographic groups. In this Series paper, we provide a brief overview of AI applications in cardiovascular health care, discuss stages of algorithm development and associated sources of bias, and provide examples of harm from biased algorithms. We propose strategies that can be applied during the training, testing, and implementation of AI algorithms to mitigate bias so that all those at risk for or living with cardiovascular disease might benefit equally from AI., Competing Interests: Declaration of interests AP has received research support from the National Institutes of Health; received grant funding from Applied Therapeutics and Gilead Sciences; received consulting fees for Tricog, Novo Nordisk, Bayer, Medtronic, Edward Lifesciences, Cytokinetics, Roche, Sarfez Pharma, Science37, Rivus, Axon Therapies, Alleviant, and Lilly; received non-financial support from Pfizer and Merck; participated on data and safety monitoring boards for Bayer, Cytokinetics, Novo Nordisk, and Medtronic; and is a consultant for Palomarin with stocks compensation. HCGV and AM declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Randomized controlled trials are the gold standard for determining treatment efficacy in medicine. To deter harmful practices such as p-hacking and hypothesizing after the results are known, any analysis of subgroups and secondary outcomes must be documented and pre-specified. However, they can still introduce bias (and routinely do) if they are not treated with the same consideration as the primary analysis., Methods: We describe several sources of bias that affect subgroup and secondary outcome analyses using published randomized trials and causal directed acyclic graphs (DAGs)., Results: We use the RECOVERY and START trials to elucidate sources of bias in analyses of subgroups and secondary outcomes. Chance imbalance can occur if the distribution of prognostic variables is not sought for any given subgroup analysis as for the main analysis. This differential distribution of prognostic variables can also occur in analyses of secondary outcomes. Selection bias can occur if the subgroup variable is causally related to staying in the trial. Given loss to follow up is not normally addressed in subgroups, attrition bias can pass unnoticed in these cases. In every case, the solution is to take the same considerations for these analyses as we do for primary analyses., Conclusions: Approval of treatments and clinical decisions can occur based on results from subgroup or secondary outcome analyses. Thus, it is important to give them the same treatment as primary analyses to avoid preventable biases., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Background: Epidemiological studies of long-term exposure to outdoor air pollution have consistently documented associations with morbidity and mortality. Air pollution exposure in these epidemiological studies is generally assessed at the residential address, because individual time-activity patterns are seldom known in large epidemiological studies. Ignoring time-activity patterns may result in bias in epidemiological studies. The aims of this paper are to assess the agreement between exposure assessed at the residential address and exposures estimated with time-activity integrated and the potential bias in epidemiological studies when exposure is estimated at the residential address., Main Body: We reviewed exposure studies that have compared residential and time-activity integrated exposures, with a focus on the correlation. We further discuss epidemiological studies that have compared health effect estimates between the residential and time-activity integrated exposure and studies that have indirectly estimated the potential bias in health effect estimates in epidemiological studies related to ignoring time-activity patterns. A large number of studies compared residential and time-activity integrated exposure, especially in Europe and North America, mostly focusing on differences in level. Eleven of these studies reported correlations, showing that the correlation between residential address-based and time-activity integrated long-term air pollution exposure was generally high to very high (R > 0.8). For individual subjects large differences were found between residential and time-activity integrated exposures. Consistent with the high correlation, five of six identified epidemiological studies found nearly identical health effects using residential and time-activity integrated exposure. Six additional studies in Europe and North America showed only small to moderate potential bias (9 to 30% potential underestimation) in estimated exposure response functions using residence-based exposures. Differences of average exposure level were generally small and in both directions. Exposure contrasts were smaller for time-activity integrated exposures in nearly all studies. The difference in exposure was not equally distributed across the population including between different socio-economic groups., Conclusions: Overall, the bias in epidemiological studies related to assessing long-term exposure at the residential address only is likely small in populations comparable to those evaluated in the comparison studies. Further improvements in exposure assessment especially for large populations remain useful., (© 2024. The Author(s).)

Objective: To summarize the characteristics of pharmacoepidemiologic research involving diabetes patients, which were published in recent years, in terms of study design and analysis, and develop an identification process for time-related biases in pharmacoepidemiologic research. Methods: PubMed, Embase, CNKI and Wanfang were used for a systematical literature retrieval of relevant study papers published between January 1,2012 and September 26, 2022. Literature screening and data extraction were performed independently by two reviewers. Based on the mechanisms of different time-related biases and the characteristics of included study papers in terms of study design and analysis methods, an identification process for all types of time-related biases was developed. Results: A total of 281 study papers were included, of which 58 (20.64%) specifically mentioned certain time-related biases considered in the study. Based on the scoping review results, key points to identify time-related biases were summarized, involving data source, study design, control selection, comparator drugs, matching the duration of diabetes, identification of the washout period, identification of the induction/latency period, identification of the initiation of follow-up, identification of time window, statistical analysis methods, sensitivity analysis, and other design and analytical elements, in the identification process for time-related biases in pharmacoepidemiologic research. Conclusions: Time-related biases are common in pharmacoepidemiologic research and might significantly impact the study results. Based on scoping review results, this study further developed an identification process for time-related biases in pharmacoepidemiologic research, which will help researchers identify and avoid time-related biases and improve the reliability of related evidence in pharmacoepidemiologic research.

While undisputedly important, and part of any systematic review (SR) by definition, evaluation of the risk of bias within the included studies is one of the most time-consuming parts of performing an SR. In this paper, we describe a case study comprising an extensive analysis of risk of bias (RoB) and reporting quality (RQ) assessment from a previously published review (CRD42021236047). It included both animal and human studies, and the included studies compared baseline diseased subjects with controls, assessed the effects of investigational treatments, or both. We compared RoB and RQ between the different types of included primary studies. We also assessed the "informative value" of each of the separate elements for meta-researchers, based on the notion that variation in reporting may be more interesting for the meta-researcher than consistently high/low or reported/non-reported scores. In general, reporting of experimental details was low. This resulted in frequent unclear risk-of-bias scores. We observed this both for animal and for human studies and both for disease-control comparisons and investigations of experimental treatments. Plots and explorative chi-square tests showed that reporting was slightly better for human studies of investigational treatments than for the other study types. With the evidence reported as is, risk-of-bias assessments for systematic reviews have low informative value other than repeatedly showing that reporting of experimental details needs to improve in all kinds of in vivo research. Particularly for reviews that do not directly inform treatment decisions, it could be efficient to perform a thorough but partial assessment of the quality of the included studies, either of a random subset of the included publications or of a subset of relatively informative elements, comprising, e.g. ethics evaluation, conflicts of interest statements, study limitations, baseline characteristics, and the unit of analysis. This publication suggests several potential procedures., (© 2024. The Author(s).)

Desired fertility measures are routinely collected and used by researchers and policy makers, but their self-reported nature raises the possibility of reporting bias. In this paper, we test for the presence of such bias by comparing responses to direct survey questions with indirect questions offering a varying, randomized, degree of confidentiality to respondents in a socioeconomically diverse sample of Nigerian women ([Formula: see text]). We find that women report higher fertility preferences when asked indirectly, but only when their responses afford them complete confidentiality, not when their responses are simply blind to the enumerator. Our results suggest that there may be fewer unintended pregnancies than currently thought and that the effectiveness of family planning policy targeting may be weakened by the bias we uncover. We conclude with suggestions for future work on how to mitigate reporting bias., Competing Interests: Competing interests statement:The authors declare no competing interest.

Background: The Foods with Function Claim was introduced in Japan in April 2015 to make more products available that are labeled with health functions. A product's functionality of function claims must be explained by the scientific evidence presented in clinical trials (CTs) or systematic reviews, but the quality of recent CTs is unclear. The purpose of this study was to evaluate the risk of bias (RoB) using "a revised tool to assess risk (RoB 2)" published in 2018 for notifications based on all recent CTs published on the Consumer Affairs Agency website., Methods: A total of 38 submitted papers based on CTs that were published on the Consumer Affairs Agency website during the period from 1 January 2023 to 30 June 2024 were eligible. The RoB 2 tool provides a framework for considering the risk of bias in the findings of any type of randomized trial. This tool with five domains was used to evaluate the quality of research methods., Results: Eligible CTs were assessed as "low risk" (11%, n = 4), "medium risk" (13%, n = 5), and "high risk" (76%, n = 29). A number of highly biased papers were published. Bias occurred in all five domains, especially "bias in selection of the reported result (Domain 5)", which was the most serious ("high risk"; 75%). For elements correlated with RoB, there was no significant difference ( p = 0.785) in the RoB 2 score between for-profit and academic research in the author's affiliated organization. There was no significant difference ( p = 0.498) in the RoB score between the published year categories of 2000-2019 and 2020-2024, and no significant difference ( p = 0.643) in the RoB score between English and Japanese language publications., Conclusion: Overall, the quality of the latest CTs submitted after 2023 was very low, occurring in all five domains, and was most serious for "bias in selection of the reported result (Domain 5)".

Background: Normal pressure hydrocephalus (NPH) occurs when the brain ventricles expand, causing a triad of gait, cognitive, and urinary impairment. It can occur after a clear brain injury such as trauma, but can also occur without a clear cause (termed idiopathic, or iNPH). Non-randomised studies have shown a benefit from surgically diverting ventricular fluid to an area of lower pressure by cerebrospinal fluid (CSF)-shunting in iNPH, but historically there have been limited randomised controlled trial (RCT) data to confirm this., Objectives: To determine the effect of CSF-shunting versus no CSF-shunting in people with iNPH and the frequency of adverse effects of CSF-shunting in iNPH., Search Methods: We searched the Cochrane Dementia and Cognitive Improvement Group's register, Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (Ovid SP), Embase (Ovid SP), PsycINFO (Ovid SP), CINAHL (EBSCOhost), Web of Science Core Collection (Clarivate), LILACS (BIREME), ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry Platform on 15 February 2023., Selection Criteria: We included only RCTs of people who had symptoms of gait, cognitive, or urinary impairment with communicating hydrocephalus (Evans index of > 0.3) and normal CSF pressure. Control groups included those with no CSF shunts or those with CSF shunts that were in 'inactive' mode., Data Collection and Analysis: We used standard Cochrane methodological procedures. Where necessary, we contacted study authors requesting data not provided in the papers. We assessed the overall certainty of the evidence using GRADE., Main Results: We included four RCTs, of which three were combined in a meta-analysis. The four RCTs included 140 participants (73 with immediate CSF-shunting and 67 controls who had delayed CSF-shunting) with an average age of 75 years. Risk of bias was low in all parallel-group outcomes evaluated apart from gait speed, cognitive function (general cognition and Symbol Digit Test) (some concerns) and adverse events, which were not blind-assessed. CSF-shunting probably improves gait speed at less than six months post-surgery (standardised mean difference (SMD) 0.62, 95% confidence interval (CI) 0.24 to 0.99; 3 studies, 116 participants; moderate-certainty evidence). CSF-shunting may improve qualitative gait function at less than six months post-surgery by an uncertain amount (1 study, 88 participants; low-certainty evidence). CSF-shunting probably results in a large reduction of disability at less than six months post-surgery (risk ratio 2.08, 95% CI 1.31 to 3.31; 3 studies, 118 participants; moderate-certainty evidence). The evidence is very uncertain about the effect of CSF-shunting on cognitive function at less than six months post-CSF-shunt surgery (SMD 0.35, 95% CI -0.04 to 0.74; 2 studies, 104 participants; very low-certainty evidence). The evidence is also very uncertain about the effect of CSF-shunt surgery on adverse events (1 study, 88 participants; very low-certainty evidence). There were no data regarding the effect of CSF-shunting on quality of life., Authors' Conclusions: We found moderate-certainty evidence that CSF-shunting likely improves gait speed and disability in iNPH in the relative short term. The evidence is very uncertain regarding cognition and adverse events. There were no longer-term RCT data for any of our prespecified outcomes. More studies are required to improve the certainty of these findings. In addition, more information is required regarding patient ethnicity and the effect of CSF-shunting on quality of life., (Copyright © 2024 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.)