Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 10 appraisals
Journal of affective disorders
Interventions to reduce loneliness in children and adolescents (4-18 years): A systematic review and meta-analysis with narrative synthesis of study-level characteristics
Loneliness in youth is linked to poor mental and physical health, yet the effectiveness of interventions remains unclear. Given its distinct developmental presentation, this meta-analysis synthesises interventions targeting loneliness in individuals aged 4-18 to inform age-appropriate strategies. It examines the effects of interventions on loneliness and includes a narrative synthesis of intervention and sample characteristics. We conducted a systematic literature review and meta-analysis of quantitative studies up to March 2024, focusing on interventions where loneliness was the primary target in school-aged youth. Nineteen studies were included in the SLR, of which 18 were included in the meta-analysis (6 RCTs, 6 multi-cohort, and 6 single-cohort studies). RCTs showed a small, non-significant reduction in loneliness (Hedges' g = -0.20, 95% CI [-0.42, 0.02], p = .07), with social and emotional skills training interventions being most effective. Multi-cohort studies showed a negligible effect (Hedges' g = -0.01, 95% CI [-0.08, 0.07], p = .84). Single-cohort studies indicated a moderate, non-significant effect (Hedges' g = -0.55, 95% CI [-1.29, 0.18], p = .14). Interventions targeting loneliness show promise in reducing loneliness, particularly when they incorporate social and emotional learning. Future research should integrate qualitative approaches and consider loneliness within broader mental health and well-being frameworks to support the development of more comprehensive, youth-centred interventions.
16 June 2026
Read appraisal →PloS one
A systematic review and meta-analysis on achievement emotions, working memory and student-teacher relationship during second language learning in primary school
Learning is a multidimensional process resulting from the interaction between cognitive and emotional factors within the learning context; in this respect the quality of the student-teacher relationship plays a significant role. Although the literature suggests that cognitive processes and emotions experienced during learning and task performing play a central role in academic achievement, it remains unclear how these factors interact with socio-affective factors in explaining academic performance, particularly in second language (L2) learning from primary school. This systematic review and meta-analysis focused on the studies that jointly or individually investigated the role of emotional factors (achievement emotions), socio-affective factors (student-teacher relationship) and cognitive factors (working memory) in L2 learning during primary school. Our sample contained 19 primary studies with 5,340 participants involved in at least one of the factors of our interest. 16 out of 19 studies were included in the meta-analysis. Our results showed a positive correlation between working memory and L2 learning, differentiated effects of achievement emotions, with a significant negative association with anxiety, and a small but positive association with enjoyment. The student-teacher relationship was supported only by qualitative evidence, however, showing a protective effect of emotional closeness to the teacher in the learning process in the presence of negative emotions such as anxiety. Findings support the importance of integrating cognitive, emotional, and relational factors to understand L2 learning in primary school. Further empirical research focusing on positive emotions and relational dynamics in different educational contexts is needed.
28 May 2026
Read appraisal →PloS one
Investigating ChatGPT-mediated mind mapping to facilitate EFL learners' reading comprehension
Mastering Reading Comprehension (RC) is a significant challenge for English as a Foreign Language (EFL) learners. This quasi-experimental mixed-methods study examined the potential effectiveness of a ChatGPT-mediated mind mapping technique in enhancing RC among EFL students at a public university in Saudi Arabia. Sixty male preparatory-year students were assigned to two groups: an experimental group (n = 30), which took part in a 10-week intervention in ChatGPT-mediated mind mapping, and a control group (n = 30), which was taught mind mapping through conventional methods. Data were gathered through pre- and post-tests of RC together with semi-structured interviews. Post-test RC scores were significantly higher in the experimental group than in the control group (U = 180.00, p < .001), with a medium-to-large effect size (r = 0.52). The qualitative data showed that students found the technique useful for breaking down complex ideas and for making the relationships between concepts in the text visible. At the same time, they reported difficulties with the accuracy of the AI output, with comprehending dense content, and with technology access. Read through the lenses of Sociocultural Theory and Cognitive Load Theory, the findings suggest that ChatGPT-mediated mind mapping can serve as a useful pedagogical tool for supporting RC. Teachers are therefore encouraged to incorporate the technique into their instructional practice while offering the support needed to address the challenges identified here.
21 May 2026
Read appraisal →Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Empowerment gain and causal model construction: children and adults are sensitive to controllability and variability in their causal interventions
Learning about the causal structure of the world is a fundamental problem for human cognition. Causal models and especially causal learning have proved to be difficult for large pretrained models using standard techniques of deep learning. In contrast, cognitive scientists have applied advances in our formal understanding of causation in computer science, particularly within the causal Bayes net formalism, to understand human causal learning. In the very different tradition of reinforcement learning (RL), researchers have described an intrinsic reward signal called 'empowerment' which maximizes mutual information between actions and their outcomes. Empowerment may be an important bridge between classical Bayesian causal learning and RL and may help to characterize causal learning in humans and enable it in machines. If an agent learns an accurate causal world model, they will necessarily increase their empowerment, and increasing empowerment will lead to a more accurate causal world model. Empowerment may also explain distinctive features of children's causal learning, as well as providing a more tractable computational account of how that learning is possible. In an empirical study, we systematically test how children and adults use cues to empowerment to infer causal relations and design effective causal interventions. This article is part of the theme issue 'World models in natural and artificial intelligence'.
15 May 2026
Read appraisal →European journal of pediatrics
Metaphorical perceptions of secondary school students regarding the concept of generative artificial intelligence
UNLABELLED: The rapid integration of generative artificial intelligence (GenAI) tools, such as ChatGPT, into educational contexts has raised important questions regarding how adolescents conceptualize and make sense of these technologies. Understanding students' perceptions is essential for developing age-appropriate, ethical, and pedagogically sound approaches to AI use in secondary education. This descriptive qualitative study employed a phenomenological approach and metaphor analysis to explore secondary school students' perceptions of generative artificial intelligence. The study sample consisted of 332 students aged 14-18 years from four secondary schools in Türkiye. Data were collected using an open-ended prompt ("Generative artificial intelligence is like … because …") and analyzed through content analysis. Metaphors were categorized based on shared semantic and conceptual features, and inter-rater reliability was established using Cohen's kappa (κ = 0.92). Analysis revealed ten metaphor categories clustered under five overarching themes: generative artificial intelligence as (1) a source of knowledge, (2) a teaching and guiding entity, (3) a supportive and assisting tool, (4) a reflection of human intelligence, and (5) a dual-purpose (beneficial-risky) technology. Students most frequently conceptualized GenAI as a comprehensive knowledge source (e.g., book, encyclopedia) and as a human-like cognitive entity (e.g., brain, wise person). At the same time, metaphors reflecting ethical awareness and potential risks, such as misuse and overreliance, were also identified. The findings indicate that secondary school students hold multifaceted and nuanced perceptions of generative artificial intelligence, encompassing both educational opportunities and ethical concerns. These results highlight the importance of integrating AI literacy into secondary education in ways that promote critical thinking, responsible use, and awareness of GenAI's limitations alongside its potential benefits. CONCLUSION: It was determined that secondary school students perceive generative artificial intelligence ambivalently as both a useful tool and a source of ethical and emotional concern, highlighting the need for developmentally appropriate artificial intelligence literacy approaches. WHAT IS KNOWN: • GenAI tools such as ChatGPT are increasingly integrated into educational contexts and have the potential to support personalized learning, information access, and student engagement. • Existing research has primarily focused on educators' perspectives or higher education settings, while studies examining adolescents' perceptions of GenAI remain limited. WHAT IS NEW: • This study provides empirical evidence on secondary school students' metaphorical perceptions of generative artificial intelligence within a K-12 context. • Findings reveal that adolescents conceptualize GenAI in multifaceted ways, including as a knowledge source, teaching and guiding entity, supportive tool, reflection of human intelligence, and a dual-purpose (beneficial-risky) technology.
10 May 2026
Read appraisal →Behavior research methods
Neural cognitive diagnosis modeling incorporating response times
Cognitive diagnosis is a fundamental issue in the field of intelligent education, aiming to identify students' mastery of specific knowledge concepts. With computerized testing, response time (RT) is a process data that can be collected. Incorporating RT in cognitive diagnosis assessment can enhance diagnostic accuracy. However, RT is only considered in traditional statistical cognitive diagnosis models. Compared with traditional statistical diagnostic models, cognitive diagnosis models based on neural networks have advantages such as high precision and strong generalization ability. Therefore, this paper proposes a JRT-NCD (joint response times neural cognitive diagnosis) model that uses neural networks to model the complex nonlinear interactions between exercises and students and incorporates RT as a new feature to refine diagnostic results on student abilities. Research findings on three datasets of PISA2012, 2MFC, and ASSIST09 indicate that: (1) In comparison with traditional statistical models, neural networks have better fitting capabilities for real complex nonlinear data; (2) compared to the NCD model that disregards RT, JRT-NCD achieves higher diagnostic accuracy while maintaining its interpretability, and reduces the misleading effects of "overspeed behavior" on the diagnostic results.
27 Apr 2026
Read appraisal →Proceedings of the National Academy of Sciences of the United States of America
Cumulative access to print books improves literacy achievement: Evidence from a five-year randomized trial in high-poverty schools
For more than a century, studies have shown that children who grow up in homes with more books achieve higher levels of academic success, yet it remains unclear whether books themselves improve learning or simply reflect broader socioeconomic advantages. Skill-development theory holds that greater access to books directly improves literacy through increased print exposure and reading practice, whereas the cultural capital account suggests books are indicators of broader family resources, including parental education, academic norms, and enrichment opportunities, that promote achievement independently of the books themselves. To provide causal evidence, we conducted a school-level randomized controlled trial of a program that builds children's home libraries. In 2018, we randomly assigned 60 high-poverty public elementary schools to treatment or control groups. Students in 30 treatment schools received four book distributions over 5 y, averaging about seven books per distribution, and prominently including high-interest and culturally relevant titles; students in 30 control schools received none. Tracking students from 2018-19 through 2022-23, we find a statistically significant intention-to-treat impact on reading achievement of d = 0.100 and a larger d = 0.207 advantage for those completing the full 5-y program. These impacts correspond to approximately 25 to 32% and 52 to 65% of a typical year's learning, respectively. The largest benefits are concentrated among students who received books across all distributions, indicating that cumulative exposure drives the strongest impacts. These findings provide evidence supporting skill-development theory and highlight a scalable strategy for improving literacy outcomes in high-poverty urban schools.
26 Apr 2026
Read appraisal →PloS one
Cognitive load and pedagogical tension in multi-platform online learning: Evidence from Chinese higher education
The proliferation of digital tools has transformed higher education into a complex, multi-platform online learning environment. This study investigates the paradoxical effects of this multi-platform environment on the student experience within Chinese higher education. Through the qualitative and quantitative data from a cross-sectional survey of 8,616 university students, we analyzed platform usage patterns, perceived benefits and challenges. The findings reveal a significant paradox: while students express positive attitudes towards platforms' educational value, acknowledging benefits like enhanced self-directed learning and improved teacher-student interaction, they concurrently report substantial practical burdens. A serial mediation model confirmed that platform multiplicity increases extraneous cognitive load, which in turn elevates tool fatigue, ultimately leading to a more negative perception of the learning experience. This study identifies a core "pedagogical tension" between the intended benefits of educational technology and the lived reality of a fragmented, high-friction user experience that encourages instrumental engagement over deep learning. These findings underscore the urgent need for institutions and instructors to adopt a more strategic, integrated approach to educational technology to reduce fragmentation and prioritize a seamless student learning experience.
25 Apr 2026
Read appraisal →PloS one
Successful student learning outcomes in Moroccan higher education: Causal configurations of pedagogical, motivational, and ICT conditions using fuzzy-set Qualitative Comparative Analysis (fsQCA)
As the demand for better educational quality and improved student performance grows, institutions face increasing challenges in making their teaching methods more effective to ensure successful learning outcomes. Most practical recommendations tend to focus on isolated effects, but learning success usually results from interconnected factors that work together. Drawing on constructivist Learning Theory, this study examines pedagogical and motivational factors that can positively impact learning results in higher education within Moroccan universities. The main goal is to identify and evaluate the nonlinear individual effects and the interactive causal configurations involving multiple conditions, such as teacher motivation, pedagogical leadership, self-efficacy, instructional innovation, ICT use, and student motivation, on learning outcomes. Empirical data were gathered through a questionnaire completed by 349 Moroccan university students, using measurement scales for key variables. The analysis employed the fuzzy-set Qualitative Comparative Analysis (fsQCA) method, which helps identify different combinations and causal pathways that lead to high academic achievement. Findings suggest that excellent learning outcomes are not caused by a single factor but by the interaction of several interdependent conditions. Different "recipes" can produce similar strong results. Certain combinations, especially those with strong teacher motivation, effective leadership, and strategic ICT use, proved to be reliable configurations, showing that technology is most impactful when integrated into supportive pedagogical and motivational environments. These results can help redefine and evaluate integrated educational policies, considering the complex interactions among individual, pedagogical, and technological factors. This approach promotes more effective and equitable learning environments through coherent bundles of mutually reinforcing interventions, instead of isolated efforts. Ultimately, this research enables educators and policymakers to develop more targeted strategies, utilize resources more efficiently, and improve overall educational effectiveness.
23 Apr 2026
Read appraisal →NeuroImage
Convergent neural signatures of optimal creative performance: A systematic review and meta-analysis
The neural architecture that supports optimal creative performance across diverse contexts remains unclear. To address this question, we conducted a quantitative meta-analysis to identify convergent patterns of brain activation associated with enhanced creativity and to examine their relationships with behavioral improvements. A total of 33 neuroimaging studies involving 965 participants were included, encompassing four enhancement contexts: creativity training, domain-specific expertise, trait-level creativity, and positive stimulus conditioning. Across these contexts, superior creative performance (Hedges' g = 0.668) was consistently characterized by increased activation in the left middle frontal gyrus (LMFG), left superior frontal gyrus (LSFG), and left inferior parietal gyrus (LIPG), together with decreased activation in the right precuneus (95 % CI [0.508, 0.828]). Meta-regression analyses revealed that longer intervention duration and greater professional experience predicted stronger LSFG and LIPG activation, whereas age and sex ratio showed no significant effects. LSFG activation was attenuated during convergent thinking tasks, suggesting task-specific modulation of creative neural circuits. These findings provide systematic evidence for a convergent neural signature of superior creative performance across multiple enhancement pathways, offering empirical targets for future training and neuromodulation-based interventions to optimize creative potential.
17 Apr 2026
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