Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 22 appraisals
Seminars in fetal & neonatal medicine
Intraventricular hemorrhage in preterm infants: A systematic review of risk- and outcome-prediction models
Intraventricular hemorrhage (IVH) is a major complication of prematurity and one of the top causes of mortality and neurodevelopmental impairment. We conducted a systematic review of PubMed, Scopus, and Web of Science (From 1980 to 2025), identifying 40 studies evaluating prediction models (regression and machine learning) for risk of IVH occurrence and short- and long-term outcomes in preterm infants with IVH. Across these published studies, IVH risk prediction models included combinations of perinatal clinical variables, physiologic and hemodynamic indices, and serum biomarkers. Outcome-prediction models likewise varied. IVH grade was commonly included, with varying inclusion of comorbidities and neuroimaging-based injury markers. Most models performed acceptably, with machine-learning models showing better discrimination in larger datasets. However, the generalizability of the models is limited by heterogeneity in predictors, limited sample sizes, and inconsistent timing of predictor measurements. IVH severity remained the most consistent predictor across all outcome-prediction models. Despite promising performance assessments, clinical relevance is limited due to the infrequent reporting of model calibration, internal validation, and external validation. Future research that standardizes predictor definitions, leverages multicenter cohorts, and ensures thorough validation can advance early IVH risk and outcome-prediction models, thereby meaningfully improving clinical relevance and neonatal care.
2 Aug 2026
Read appraisal →European journal of pediatrics
Contemporary physiotherapy interventions for balance rehabilitation in children with Down syndrome: a systematic review of randomized controlled trials
Children with Down syndrome commonly present with impaired balance and postural control due to musculoskeletal, sensory, and neuromotor deficits, which may negatively affect functional mobility and participation in daily activities. Over the last decade, a variety of contemporary physiotherapy interventions have been investigated to improve balance in this population. The aim of this systematic review was to synthesize evidence from randomized controlled trials evaluating physiotherapy interventions targeting balance rehabilitation in children with Down syndrome. A systematic search was conducted in PubMed and Scopus for studies published between 2015 and 2025. Randomized controlled trials investigating physiotherapy-related interventions targeting balance in children and adolescents with Down syndrome were included. Two independent reviewers performed study selection and data extraction. Methodological quality was assessed using the Physiotherapy Evidence Database (PEDro) scale. A total of 14 randomized controlled trials involving 462 participants were included. The included interventions comprised isokinetic training, trampoline-based plyometric exercise, Pilates, dual-task exercise, hippotherapy, whole-body vibration, foot muscle strengthening, swimming programs, kinesiotaping, and vestibular stimulation. Improvements in balance-related outcomes were observed across a broad range of physiotherapy interventions, particularly when approaches were combined with conventional physiotherapy programs. Conclusion: Contemporary physiotherapy interventions appear to be associated with improvements in balance-related outcomes in children with Down syndrome. The findings of this review support the integration of technology-assisted and task-oriented rehabilitation approaches into pediatric physiotherapy practice. However, the overall methodological quality of the included studies ranged from fair to high, and further large-scale, high-quality RCTs with long-term follow-up are required to strengthen the current evidence base.
28 July 2026
Read appraisal →Science advances
Curiosity-driven development of action and language in robots through self-exploration
Infants acquire language with generalization from minimal experience, whereas large language models require billions of training tokens. What underlies efficient development in humans? We investigated this problem through experiments wherein robotic agents learn to perform actions associated with imperative sentences (e.g., push red cube) via curiosity-driven self-exploration. Our approach amortizes active inference using Q-learning, enabling intrinsically motivated developmental learning. The simulations reveal key findings corresponding to observations in developmental psychology. (i) Generalization improves markedly as the scale of compositional elements increases. (ii) Curiosity-driven exploration enables faster learning. (iii) Rote pairing of sentences and actions precedes compositional generalization. (iv) Exception handling induces U-shaped developmental performance, a pattern like representational redescription in child language learning. These results suggest that curiosity-driven active inference accounts for how intrinsically motivated sensorimotor-linguistic learning supports scalable compositional generalization and exception handling in humans and artificial agents.
25 July 2026
Read appraisal →Journal of speech, language, and hearing research : JSLHR
Language-Common and Language-Specific Error Patterns in Children With Speech Sound Disorders: A Systematic Review
OBJECTIVES: This systematic review synthesized cross-linguistic evidence on speech error patterns in children with speech sound disorders (SSDs), focusing on percent consonants correct (PCC), SODA (substitution, omission, distortion, and addition) error profiles, and phonological processes, as well as factors contributing to variations in error patterns. METHOD: Comprehensive searches were conducted in PubMed, CINAHL Ultimate, Scopus, Web of Science, and Linguistics and Language Behavior Abstracts in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Eligible studies included empirical research on children with phonological, articulation, or functional SSDs that reported quantitative error analyses. Twenty-eight studies met the inclusion criteria. Methodological quality, evaluated using a 16-item framework, ranged from 50.0% to 100.0% (M = 82.7%). RESULTS: The 28 studies spanned nine languages (English, German, Spanish, Portuguese, Italian, French, Turkish, Korean, and Chinese), including three dialects each of Spanish and Chinese and two dialects of Portuguese. Reported PCC values (typically 65.0%-85.0%) indicated predominantly mild-moderate to moderate impairment. Substitution errors were the most prevalent across languages, followed by omissions and distortions. Both language-common and language-specific phonological processes were documented. DISCUSSION: The findings indicate that PCC is generally comparable across languages, whereas SODA error profiles and phonological processes reflect both cross-linguistic similarities and language-specific characteristics. Phonological processes, in particular, exhibit greater cross-linguistic variation. Collectively, these results emphasize the need for culturally responsive diagnostic practices and highlight the importance of developing cross-linguistic frameworks to guide the assessment of SSDs. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.32649549.
10 July 2026
Read appraisal →PloS one
Long-term effects following prenatal cocaine exposure: A systematic review.
Cocaine use represents a global public-health concern, and children's exposure to this substance is receiving growing attention. Despite the importance of this phenomenon, efforts to isolate cocaine-specific long-term effects are affected by the limited availability of human cohorts followed into adulthood and by the influence of environmental factors and co-exposures. Addressing ongoing debates in the literature, this systematic review synthesizes human evidence on long-term outcomes following prenatal cocaine exposure (PCE), from infancy to early adulthood. A comprehensive search of PubMed and Scopus from inception to August 2025 identified 26 eligible studies. Results suggest that across maturational stages, PCE is consistently associated with early developmental effects (including smaller head circumference and motor delays), deficits in visuospatial, language and executive functions, focal neuroimaging alterations (white-matter microstructure and task-related functional recruitment), growth deficits, and elevated externalizing behaviours. However, evidence is characterised by heterogeneity in exposure assessment, frequent prenatal polysubstance exposure, socioeconomic confounding, caregiving instability and small neuroimaging samples. Overall, this review suggests that PCE is linked to a broad spectrum of detrimental effects and that some biological vulnerabilities associated with PCE may persist. Nonetheless, supportive postnatal environments may mitigate developmental disadvantages and promote better trajectories for affected children. These findings underscore the need for integrated public-health and clinical strategies that combine prevention of prenatal substance use with family-focused postnatal supports.
28 June 2026
Read appraisal →PloS one
Factors associated with resilience among parents of children with autism spectrum disorder: A systematic review
Parents of children with autism spectrum disorder (ASD) experience ongoing caregiving demands and challenges that may contribute to their general well-being. Research has shown that resilience enables parents to adapt to these challenges; however, existing evidence on associated factors toward resilience among these parents remains fragmented. This systematic review aimed to identify factors associated with resilience among parents of children with ASD. We conducted a PRISMA 2020-guided systematic review on studies published between January 2019 and May 2025 using Web of Science, Scopus, and PubMed by applying predefined search terms and Boolean operators. Studies examining factors associated with resilience among parents of children with ASD aged under 18 years were included in this review. We also used the Mixed Methods Appraisal Tool 2018 to assess the quality of these studies. Findings were synthesised narratively using thematic analysis. From the 13 selected studies, five themes were identified as determinants of resilience among parents, i.e., sociodemographic and economic factors; child-related characteristics; parenting well-being and distress; psychological factors and coping styles; and social support and family relationships. Most included studies were cross-sectional and utilised different measurement tools, which may limit causal inference and comparability. As a conclusion, parental resilience was found to be influenced by psychological, social, and contextual factors. Strengthening coping resources and social support may enhance parental adaptation and family well-being. Along these lines, multi-level and culturally sensitive interventions are thus needed to inform strategies to foster resilience among parents of children with ASD. The review was registered with PROSPERO (CRD420251034348). The author(s) received no specific funding for this work.
23 June 2026
Read appraisal →European journal of pediatrics
Subtypes in developmental coordination disorder: what do we know so far? A systematic review.
UNLABELLED: Developmental coordination disorder (DCD) is a highly heterogeneous disorder. This systematic review examined whether statistically derived clusters can effectively distinguish subgroups of children with DCD. Web of Science, Scopus, PubMed, Embase, and PsycInfo were systematically searched (CRD420251237685) using controlled terminology and free-text terms. Studies were eligible if they included children (aged 0-18 years) with DCD with(out) comorbidities and employed statistical clustering to identify subtypes. Methodological quality was assessed using an adapted version of the Critical Appraisal Skills Programme and certainty of the evidence with the Grading of Recommendations Assessment, Development and Evaluation. Ten of the 1719 search results were included, three of which included both children with DCD and typical development. Two studies explored clusters unidimensionally (motor-only and mental health-only). Eight studies included multiple domains of functioning: motor (n = 8), sensory functions (n = 5), fitness (n = 3), cognitive functions (n = 3), executive functions (n = 2), mental health (n = 1), and participation (n = 1). Studies identified between four (n = 4) and six (n = 1) subtypes, which primarily reflected gradients of severity rather than distinct domain-specific profiles. The overall certainty of evidence for distinct subtypes in DCD was rated low to very low. CONCLUSION: Evidence suggests that DCD is better conceptualized as a spectrum of pervasiveness rather than discrete subtypes. Existing findings lack consistency across studies due to methodological shortcomings and variable measurement domains. Although evidence-based clinical subtypes cannot yet be recommended, future research should prioritize subtyping studies focused on primary symptoms to better identify potential phenotypes within the DCD population. WHAT IS KNOWN: • DCD is a heterogeneous condition, and identifying discrete subtypes is a long-standing research goal to improve clinical support. • Researchers have proposed various motor and non-motor profiles, but no consensus exists on a definitive subtyping model. WHAT IS NEW: • This review found no consistent discrete subtypes, suggesting DCD is better viewed as a spectrum of pervasiveness rather than categories. • Future research should focus on subtyping primary motor symptoms to determine whether distinct, stable subgroups exist within the broader DCD population.
22 June 2026
Read appraisal →Progress in neuro-psychopharmacology & biological psychiatry
Neural correlates of late talking: A systematic review of electrophysiological and neuroimaging studies.
BACKGROUND: Late talking (LT), a delay in expressive vocabulary in early childhood, affects a significant minority of toddlers and can be a precursor to persistent language and literacy impairments. While behavioral profiles are well-documented, a systematic synthesis of its underlying neurobiology is lacking. This systematic review aimed to identify, evaluate, and synthesize evidence from electrophysiological (EEG) and neuroimaging (MRI) studies on the neural correlates of late talking in children. METHODS: We conducted a systematic search of Scopus, Web of Science, and PubMed from inception to September 2025, following PRISMA guidelines. Studies investigating children formally identified as late talkers without comorbid neurological or global developmental conditions, using EEG/ERP or MRI modalities, were included. Risk of bias was assessed using the Joanna Briggs Institute (JBI) critical appraisal tool. RESULTS: Sixteen studies (8 EEG, 8 neuroimaging) comprising 231 LT children in EEG studies and 315 in neuroimaging studies were included. EEG studies revealed a neurodevelopmental cascade, beginning with atypical oscillatory activity (increased frontal gamma power) and deficits in auditory discrimination (reduced Mismatch Negativity), progressing to higher-order impairments in phonological (absent PMN) and lexical-semantic (altered N400) processing. Neuroimaging studies consistently identified structural and functional anomalies within a distributed perisylvian network, including reduced gray matter in left temporal regions, atypical right-hemispheric lateralization, reduced activation in cortical-subcortical circuits, and altered white matter connectivity. These neural markers demonstrated significant predictive value for later language outcomes. CONCLUSION: Late talking is a clear neurodevelopmental disorder with a cascading pattern of neural dysfunction. The identified neural signatures are not just findings but have strong clinical potential as biomarkers for early identification and prognosis. This evidence advocates for a shift to a precision medicine approach, opening the door to novel, neurobiologically-informed interventions like neuromodulation that target the underlying brain circuits.
20 June 2026
Read appraisal →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 →International journal of medical informatics
Machine learning approaches to identifying neurodevelopmental disorders using social media data: a systematic review
BACKGROUND: Neurodevelopmental disorders (NDDs), such as autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), often emerge in early childhood and can significantly impact social, academic, and emotional functioning. Early identification is critical to improving long-term outcomes, yet traditional diagnostic processes are time-consuming and resource-intensive. As social media becomes an integral part of daily life, user-generated content offers a novel source of behavioral and linguistic data that may support early detection. Advances in artificial intelligence (AI) and machine learning (ML) now make it possible to analyze these large-scale data streams for clinical insights. METHODS: A comprehensive search was performed across five databases-PubMed, Scopus, Web of Science, IEEE Xplore, and ACM Digital Library-from inception up to July 2025. Studies were included if they used AI or ML methods to analyze social media data for detecting NDDs. Data extraction focused on platform type, targeted disorder, dataset size, ML technique, and diagnostic performance. RESULTS: Nineteen studies met the inclusion criteria. Most focused on ASD and ADHD, using platforms such as Reddit, Twitter, YouTube, and Facebook. ML models achieved moderate to high classification performance, with F1-scores ranging from approximately 0.48 to 0.89 depending on the data type and disorder. Video-based models showed particular promise in identifying nonverbal behavioral markers. However, research on other NDDs remains limited, and methodological heterogeneity, small sample sizes, and ethical challenges persist. CONCLUSION: AI-driven analysis of social media data holds significant promise for scalable, non-invasive screening of neurodevelopmental disorders. While current work largely focuses on ASD and ADHD, future research should extend to underrepresented NDDs and address concerns related to data validity, bias, and privacy. With continued advancement, these tools may serve as valuable complements to traditional diagnostic methods.
15 June 2026
Read appraisal →Journal of speech, language, and hearing research : JSLHR
Augmentative and Alternative Communication Generative Language Intervention: A Randomized Controlled Trial
PURPOSE: Children with a wide range of impairments such as cerebral palsy and childhood apraxia of speech can benefit from augmentative and alternative communication (AAC). When AAC is provided, it frequently focuses on improving basic pragmatic skills such as requesting or on early semantic skills such as vocabulary acquisition. To address this issue, the primary goal of this study was to evaluate the effects of implementing the AAC Generative Language Intervention (AAC-GLI) program on the aided expressive grammar of preschoolers with relatively intact receptive language skills who could benefit from AAC. METHOD: A randomized controlled trial was used to evaluate the results. A total of 40 children who required AAC participated in the control group, intervention group, or both groups. The families of both the control and intervention group participants received a half-day AAC workshop. The intervention group also received 28 play-based AAC-GLI sessions. Weighted mean length of utterance in symbols (W-MLUSym), which was developed specifically for aided communicators, was used to measure progress. RESULTS: The intervention group demonstrated superior effects on W-MLUSym compared with the control group. Additionally, growth modeling demonstrated that the intervention condition was a significant moderator of change over time, with children in the intervention condition having statistically significantly greater increases in W-MLUSym, while W-MLUSym for children in the control condition remained similar to baseline. DISCUSSION: AAC-GLI can be used to teach preschoolers with a range of impairments to improve their expressive grammar skills. Providing AAC intervention that focuses on grammatical growth is an important part of expressive language development for these young children.
13 June 2026
Read appraisal →Medical science monitor : international medical journal of experimental and clinical research
Impact of Gross Motor Coordination Exercises on Perceptual Processes and Praxis in Early School Children With Symptoms of Developmental Coordination Disorder: Preliminary Report of Randomized Controlled Study
BACKGROUND Physical activity has a general impact on cognitive processes, but evidence on the effects of specific exercises on particular cognitive or executive functions remains limited. Previous studies suggest that movements crossing the body's midline stimulate excitability and plasticity in the dorsolateral prefrontal cortex and superior parietal cortex. This study aimed to investigate whether such exercises produce long-term functional changes in these areas. MATERIAL AND METHODS The study involved 22 children aged 6 to 8 years with symptoms of developmental coordination disorder (DCD), divided into 2 equal groups. Both groups completed approximately 9 weeks of coordination training based on Bilateral Integration by Sheila Dobie OBE (the total diagnostic and therapeutic cycle lasted approximately 16 weeks, including a break). The intervention group performed exercises involving midline crossing, while the control group performed exercises without this element. Assessments (sensory integration and praxis tests and the bilateral motor coordination test) were conducted 3 times: before intervention, after 9-week program, and at follow-up. RESULTS Significant improvements were observed in both groups in sequencing praxis (P=0.041 in the control group; P<0.001 in the intervention group) and bilateral motor coordination (P=0.013; P=0.020), but at different rates. In the intervention group, improvements appeared after the intervention, while in the control group only at follow-up. Large effect sizes were found (η² ϵ [0.293, 0.670]), with high statistical power. No significant changes were observed in other functions. CONCLUSIONS The Bilateral Integration method improves sequencing praxis and interhemispheric integration in children with DCD symptoms. Midline-crossing exercises may yield relatively fast improvements in short-term programs.
11 June 2026
Read appraisal →JMIR research protocols
Telehealth Versus In-Person Caregiver-Mediated Behavioral Treatment for Challenging Behaviors in Children With Autism Spectrum Disorder: Protocol for COACH (Caregiver Outreach for Autism Coaching at Home) Randomized Controlled Trial
BACKGROUND: Approximately 40%-60% of children diagnosed with autism spectrum disorder (ASD) exhibit challenging behaviors such as aggression, elopement, self-injury, and property destruction that can endanger the health and safety of the child or others, often cause significant distress for families, and hinder the child's developmental progress. Although behavioral treatments grounded in the principles of applied behavior analysis have been shown to effectively reduce or eliminate these behaviors, significant gaps remain in how to deliver these interventions equitably. OBJECTIVE: This study aims to compare the efficacy of delivering in-person versus telehealth caregiver-mediated behavioral treatment for challenging behaviors in children with ASD. METHODS: The Caregiver Outreach for Autism Coaching at Home trial is a single-site, multiarm, parallel-group randomized controlled trial to evaluate the efficacy of delivering caregiver-mediated behavioral treatment for children with ASD who exhibit challenging behaviors. We aim to recruit 90 caregiver-child dyads with children with ASD aged 2 years, 0 months to 7 years, 11 months from metropolitan, suburban, and rural areas across New Mexico and the neighboring El Paso, Texas region. Following a practical functional assessment to identify the potential social-environmental variables maintaining the child's challenging behavior, caregiver-child dyads will be randomized into one of three parallel treatment arms: (1) caregiver-mediated behavioral treatment delivered via telehealth, (2) caregiver-mediated behavioral treatment delivered in person, or (3) caregiver online psychoeducation. Interventions will be delivered by clinicians in weekly 1-hour sessions in the home setting over 12 weeks. RESULTS: The study was funded in May 2022, and recruitment began in January 2024. As of March 2026, 81 caregiver-child dyads have been enrolled, with equal allocation across the 3 study groups (27 per group). Recruitment is expected to conclude in October 2026, with data analysis planned for Winter 2026 through Spring 2027. CONCLUSIONS: This study will address a critical gap in the scientific literature on scalable, family-centered approaches to safely and effectively reduce challenging behavior in children with ASD and decrease caregiver stress. Findings may inform best practices and payer policy for telehealth-delivered behavioral interventions targeting child safety and caregiver well-being.
29 May 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 →Journal of perinatal medicine
Functional neurobehaviour of the human fetus: a comprehensive framework for prenatal assessment using 4D ultrasound and AI
OBJECTIVES: To evaluate current evidence on prenatal neurobehavioural assessment using four-dimensional ultrasound (4D-US), structured scoring systems, and emerging artificial intelligence (AI) platforms, and to develop an integrated framework for early identification of neurodevelopmental vulnerability. METHODS: A narrative review of the literature from 2000 to 2025 was conducted following PRISMA-guided organisational principles to enhance transparency. Studies were eligible if they used 3D/4D ultrasound to assess fetal neurobehaviour, including spontaneous motor activity, facial expressions, or behavioural transitions. Specific tools examined included the Kurjak Antenatal Neurodevelopmental Test (KANET), prenatal General Movements Assessment (GMA), and AI-assisted behavioural analysis systems. Methodological quality was appraised using the Newcastle-Ottawa Scale and the Joanna Briggs Institute checklist. Data extraction focused on imaging protocols, behavioural parameters, scoring systems, and associations with neonatal neurological outcomes. RESULTS: Fifty eligible studies demonstrated that fetal motor sequences, movement variability, and facial expressions exhibit hierarchical maturation consistent with developmental progression of brainstem, subcortical, and cortical neural circuits. KANET parameters showed reproducible scoring and meaningful correlation with neonatal neurodevelopment, particularly in high-risk pregnancies. Prenatal general movement patterns displayed continuity with postnatal repertoires and contributed to early neurological prediction. AI-based classifiers provided objective quantification of fetal movement and facial activity, supporting automated or semi-automated assessment workflows. CONCLUSIONS: Functional neurobehavioural assessment using 4D-US, structured scoring tools, and AI-enhanced analysis is feasible, reproducible, and clinically informative. Integrating behavioural markers with neurosonographic findings and computational modelling may strengthen early detection of neurological risk and improve long-term neurodevelopmental care pathways.
27 May 2026
Read appraisal →European journal of pediatrics
Associations of socioeconomic status and nurturing environment with developmental outcomes in very preterm children without sensorimotor impairment: a secondary analysis of the INTACT study
UNLABELLED: The objective of this study is to retrospectively evaluate the associations between socioeconomic status (SES), including nurturing environment, and developmental quotients (DQ) at age 3 in children born very preterm with birth weight ≤ 1500 g. This secondary analysis used follow-up data from the Improvement of NICU Practices and Team Approach Cluster Randomized Controlled Trial. Participants born < 32 weeks' gestation without major sensorimotor impairments were stratified into three groups: 22-24, 25-27, and 28-31 weeks. Multiple linear regression evaluated the associations between prenatal SES and DQ scores of the Kyoto Scale of Psychological Development (KSPD), adjusted for sex, parity, gestational age, small for gestational age, multiple births, and facilities. Post-discharge SES variables were subsequently added to assess associations with nurturing environment. Of 2148 eligible survivors, 1978 underwent KSPD testing and 1846 caregivers completed SES questionnaires. Higher parental education was positively associated with total DQ across all groups: 22-24 weeks (β = 2.246, 95% CI 0.015-4.477), 25-27 weeks (β = 1.589, 95% CI 0.408-2.770), and 28-31 weeks (β = 1.299, 95% CI 0.315-2.282). Group childcare utilization was associated with higher total DQ: 22-24 weeks (β = 3.397, 95% CI 0.893-5.901), 25-27 weeks (β = 1.851, 95% CI 0.591-3.111), and 28-31 weeks (β = 2.617, 95% CI 1.613-3.620). These associations remained after adjustments for postnatal morbidities. CONCLUSION: Among children born very preterm without major sensorimotor impairments, parental education and group childcare utilization were independently associated with more favorable cognitive outcomes at age 3. These results suggest the importance of socioeconomic and environmental support in optimizing developmental outcomes for this vulnerable population. WHAT IS KNOWN: • Prenatal and postnatal SES are associated with developmental outcomes in both preterm and term children. In addition, daily group childcare environments influence child development in the general population. WHAT IS NEW: • Among very preterm children without major sensorimotor impairments, including those born at 22-24 weeks' gestation, parental education and group childcare utilization are independently associated with more favorable cognitive and language outcomes at age 3.
25 May 2026
Read appraisal →Proceedings of the National Academy of Sciences of the United States of America
Discovering regularity and mechanisms of word sense acquisition in childhood.
How does language use inform the emergence of word meanings in early life? Prior work in developmental psychology and the cognitive sciences typically focuses on studying word acquisition in children without specifying how different senses within a word emerge through time. To shed light on word sense acquisition, we propose a framework grounded in state-of-the-art computational methodologies of contextual word embedding to characterize how different senses of a word unfold as children acquire their lexicon. Our framework identifies word senses automatically by forming semantic clusters through natural language use, and analyzes 1,270 words from approximately 4 million utterances produced by children (19 to 144 mo) and their caretakers. The psychological validity of these senses was assessed based on a combination of dictionaries, human judgment of semantic similarity, and evaluation from a large language model. We then tested three hypotheses motivated by existing work on word sense emergence in language evolution. First, concrete senses of a word tend to emerge earlier than more abstract senses in child language. Second, word senses grow incrementally in semantic space across development. Third, algorithms of semantic chaining-how words spawn new senses by extending from existing senses-recapitulate the order of word senses in development. We find support for all three hypotheses. Our work suggests that the development of word meaning in language acquisition resembles that in language evolution and offers a converging view on the cognitive principles and mechanisms across timescales in the ontogeny and phylogeny of word sense emergence.
13 May 2026
Read appraisal →BMJ open
Multimodal personalised executive function intervention (E-Fit) for school-aged children with complex congenital heart disease in Switzerland: a randomised controlled feasibility study
OBJECTIVE: To explore the feasibility of a novel multimodal executive function intervention in school-aged children with complex congenital heart disease (cCHD). DESIGN: Single-centre, single-blinded, randomised-controlled 8-week multimodal personalised executive function intervention (E-Fit) study. Outcomes were measured throughout the intervention, post-intervention (T1) and at 4-month follow-up (T2). SETTING: Tertiary care centre between May 2022 and May 2024. PARTICIPANTS: Children 10 to 12 years (M=11.0, SD=0.9) with cCHD without a genetic diagnosis with infant open-heart surgery and reported difficulties (T-scores ≥60) on any of the summary scales of the parent- or teacher-reported Behavior Rating Inventory for Executive Function (BRIEF). INTERVENTIONS: Children with cCHD were randomly assigned to one of two groups: the intervention or the control group. The 8-week intervention was multimodal including three modalities: (1) computerised executive function (EF) training 3×20 min/week with CogniFit; (2) a weekly, remote standardised 1:1 individual EF strategy coaching; (3) analogue games played at convenience. The control group completed activity logs. FEASIBILITY MEASURES: Acceptability: Acceptance and Feasibility Scale (AFS) and coach-rated engagement during coaching sessions. Demand: Number of completed computerised training, strategy coaching and analogue game sessions. IMPLEMENTATION: E-Fit Fidelity Measurement System, assessing adherence to core components. Practicality: Retention rate. Integration: AFS integration items. Exploratory efficacy: BRIEF, neuropsychological EF testing and psychosocial variables at baseline, post-intervention (8 weeks) and at 4-month follow-up. RESULTS: We recruited 42 participants (Nfemale=20). Acceptability: The intervention was acceptable, with moderate observed engagement. Demand: median number of computerised training sessions completed was 16 of 24 sessions (67%, (IQR; 6 to 19)), all children attended all scheduled coaching sessions, analogue games were played in total a median of 9 times (IQR 4 to 14). IMPLEMENTATION: Coaching sessions could be implemented by the coaches as intended. Practicality: Overall retention rate was 90%. Integration: E-Fit was well integrable into the home setting. Exploratory efficacy favoured the intervention group with improvements in the parent-rated Behavioral Regulation Index of the BRIEF (adjusted Hedge's (gA1) = -0.408 to -0.903) and in social responsiveness (gA1 = -0.427 to -0.521) at T1 and at T2. CONCLUSIONS: E-Fit is a feasible intervention suggesting EF and social responsiveness improvements in children with cCHD. Motivational strategies to improve adherence to computerised training should be refined before a full-scale efficacy trial. TRIAL REGISTRATION NUMBER: NCT05198583.
12 May 2026
Read appraisal →IEEE transactions on bio-medical engineering
Multilevel Correlation-Aware and Modal-Aware Graph Convolutional Network for Diagnosing Neurodevelopmental Disorders
OBJECTIVE: Graph-based methods using resting-state functional magnetic resonance imaging demonstrate strong capabilities in modeling brain networks. However, existing graph-based methods often overlook inter-graph relationships, limiting their ability to capture the intrinsic features shared across individuals. Additionally, their simplistic integration strategies may fail to take full advantage of multimodal information. To address these challenges, this paper proposes a Multilevel Correlation-aware and Modal-aware Graph Convolutional Network (MCM-GCN) for the reliable diagnosis of neurodevelopmental disorders. METHODS: At the individual level, we design a correlation-driven feature generation module that incorporates a pooling layer with external graph attention to perceive inter-graph correlations, generating discriminative brain embeddings and identifying disease-related regions. At the population level, to deeply integrate multimodal and multi-atlas information, a multimodal-decoupled feature enhancement module learns unique and shared embeddings from brain graphs and phenotypic data and then fuses them adaptively with graph channel attention for reliable disease classification. RESULTS: Extensive experiments on two public datasets for Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) demonstrate that MCM-GCN outperforms other competing methods, with an accuracy of 93.11% for ASD and 76.41% for ADHD. CONCLUSION: The MCM-GCN framework integrates individual-level and population-level analyses, offering a comprehensive perspective for neurodevelopmental disorder diagnosis, significantly improving diagnostic accuracy while identifying key indicators. SIGNIFICANCE: These findings highlight the potential of the MCM-GCN for imaging-assisted diagnosis of neurodevelopmental diseases, advancing interpretable deep learning in medical imaging analysis.
6 May 2026
Read appraisal →Psychonomic bulletin & review
Speaker effects in language comprehension: An integrative model of language and speaker processing
The identity of a speaker influences language comprehension through modulating perception and expectation. This review explores speaker effects and proposes an integrative model of language and speaker processing that integrates distinct mechanistic perspectives. We argue that speaker effects arise from the interplay between bottom-up perception-based processes, driven by acoustic-episodic memory, and top-down expectation-based processes, driven by a speaker model. We show that language and speaker processing are functionally integrated through multi-level probabilistic processing: prior beliefs about a speaker modulate language processing at the phonetic, lexical, and semantic levels, while the unfolding speech and message continuously update the speaker model, refining broad demographic priors into precise individualized representations. Within this framework, we distinguish between speaker-idiosyncrasy effects arising from familiarity with an individual and speaker-demographics effects arising from social group expectations. We discuss how speaker effects serve as indices for assessing language development and social cognition, and we encourage future research to extend these findings to the emerging domain of artificial intelligence (AI) speakers, as AI agents represent a new class of social interlocutors that are transforming the way we engage in communication.
17 Apr 2026
Read appraisal →PloS one
Hybrid deep learning and feature selection approach for autism detection from rs-fMRI data
Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that is primarily characterized by deficits in social communication and restricted or repetitive behavioral patterns. Although psychologists contribute significantly to the understanding of ASD, offering insights into its cognitive, emotional, and behavioral dimensions through assessments, diagnoses, therapeutic approaches, and family support, the diagnostic process remains complex. This complexity arises from the diverse manifestations of the disorder and the challenges associated with data sharing. In addition, conventional machine learning approaches for ASD detection may struggle with high-dimensional neuroimaging data and may require careful feature engineering. Consequently, this motivated us to enhance ASD diagnosis by incorporating deep learning (DL) techniques for feature extraction alongside a modified exponential-trigonometric optimization (ETO) algorithm as a feature selection (FS) technique. The modified ETO integrates the Arithmetic Optimization Algorithm (AOA) and the Guided Learning Strategy (GLS) to improve diagnostic performance. To evaluate the effectiveness of the proposed model, we utilized resting-state functional MRI (rs-fMRI) data from the Autism Brain Imaging Data Exchange (ABIDE I). Furthermore, the performance of the proposed model was compared with that of established models. The results indicate that the proposed model achieves competitive and, in most cases, superior performance compared with the benchmark methods, demonstrating superior accuracy, sensitivity, and AUC in diagnosing ASD. On average across the three atlas-based feature sets, the proposed model has an accuracy, sensitivity, and AUC of 73%, 78%, and 79%, respectively.
9 Apr 2026
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Caregivers' early stimulation behaviors on early child development outcomes in Northern Ghana
Despite the government prioritizing Early Childhood Development (ECD) in Ghana, data on responsive caregiving is limited. This study examined the type and extent of Early Stimulation Activities (ESAs) practiced by mothers, and other caregivers and the associations between ESAs and children's development by caregiver type in Northern Ghana. Data were from a cluster-randomized controlled trial with mother-child dyads that evaluated the impact of an integrated maternal mental health and early childhood intervention program. The primary outcome was measured by the Developmental Milestone Checklist (DMC-II). Covariates included maternal report of ESAs performed by herself, child's father, and other caregivers. Linear regression analyses with cluster-adjusted standard errors were performed. Nearly 15% of mother-participants (n = 313) reported 4 + ESAs in the past 3 days. Within the last 3 days, on average, women reported 2.5 activities for themselves, 1.2 activities by the child's father, and 2 activities by other caregivers. The associations between ESAs and children's development varied by caregiver type. Maternal stimulation was positively associated with children's total development and personal-social development, early stimulation by other caregivers was positively associated with children's total development and language development, and paternal stimulation was not associated with any development domain. Other associations included receipt of postnatal care and presence of household toys. While maternal stimulation seemed particularly important, findings regarding non-primary caregivers suggest that ECD programming could also benefit from their inclusion.
5 Apr 2026
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