Search Results (5,606)

Dental caries is one of the most prevalent chronic diseases affecting older adults and remains an important, underrecognized contributor to pain, impaired nutrition, systemic illness, and reduced quality of life. Older adults access medical care more often than dental care, positioning non-dental clinicians to identify risk, initiate prevention, and facilitate timely referral. A narrative review of English-language literature was conducted using PubMed and Google Scholar. Search terms included “dental caries,” “root caries,” and “older adults.” Sources included original studies, clinical guidelines, consensus statements, and high-quality reviews, with an emphasis on relevance to older adults and applicability to non-dental clinicians. Dental caries in older adults commonly presents as root and recurrent decay and isstrongly associated with xerostomia, polypharmacy, chronic disease, functional impairment, cognitive decline, and limited access to dental care. The literature supports fluoride-based prevention, management of salivary dysfunction, dietary counseling, minimally invasive therapies such as silver diamine fluoride, and interprofessional care models. Non-dental providers play a critical role in screening, risk assessment, preventive counseling, symptom triage, and referral. Integrating oral health into routine medical care is an essential and achievable strategy to reduce morbidity and improve health outcomes in older adults. Full article

Background: Caregiver burden represents a multidimensional syndrome influenced by patient-related, relational, and contextual factors in neurological disorders. Although stroke, Parkinson’s disease (PD), and Alzheimer’s disease (AD) differ in clinical trajectory, comparative analyses of caregiver risk profiles across these conditions remain limited. Objective: This study aimed to identify sociodemographic, cognitive, and dyadic factors associated with caregiver burden in a clinical cohort, and to investigate their value for caregiver risk stratification using supervised machine learning models. Methods: In this monocentric observational cohort study, 113 patient–caregiver dyads (79 stroke, 19 PD, 15 AD) were consecutively enrolled in a neurorehabilitation setting. Patients underwent cognitive assessment with the Montreal Cognitive Assessment (MoCA), while caregivers completed the Caregiver Burden Inventory (CBI), which was considered the primary outcome measure. Caregiver burden was dichotomized into mild versus moderate-to-severe burden using established CBI cutoff thresholds. Group comparisons, correlation analyses (false discovery rate–corrected), and supervised machine learning models (logistic regression, random forest, AdaBoost, support-vector machine, naïve Bayes, and CatBoost) were performed using 5-fold stratified cross-validation repeated 10 times. Results: Disease-specific burden patterns emerged. Stroke caregivers reported higher time-dependent burden, whereas AD caregivers showed greater emotional burden (p < 0.05). No significant differences were observed in total CBI scores across groups. Lower MoCA scores were moderately associated with higher total and time-dependent burden (r up to −0.49, p < 0.001), particularly when interacting with advanced patient age. Machine learning models showed moderate performance, with AdaBoost achieving the highest accuracy (75.8%) and logistic regression and CatBoost the highest area under the receiver-operating-characteristic curve (AUC = 0.80). The most influential predictors were the age × MoCA interaction, MoCA score alone, and patient–caregiver gender concordance. Cognitive impairment, especially in older patients, and dyadic gender concordance emerged as central risk factors. Conclusions: Multidimensional assessment and early risk stratification, potentially supported by machine learning tools, may improve identification of vulnerable caregivers and guide tailored interventions. Full article

Background and Objectives: Evidence on the acute effects of caffeine in female team-sport athletes is limited. This study aimed to quantify the acute effects of caffeine on female team-sport athletes across physical performance, sport-specific performance, physiological responses, perceptual responses, and cognitive performance and determine moderators. Methods: PubMed and Web of Science were systematically searched for randomized, placebo-controlled crossover trials of acute, dose-defined caffeine in female team-sport athletes. Effect sizes were expressed as Hedges’ g and synthesized within each domain using a three-level CHE model with CR2 cluster-robust variance estimation and Satterthwaite degrees of freedom; 95% confidence intervals and prediction intervals were reported. Risk of bias (RoB 2), methodological quality (PEDro), and certainty of evidence (GRADE) were assessed. Results: Twenty-six studies were included, comprising 26 randomized, blind, placebo-controlled crossover trials. As a descriptive cross-domain summary, acute caffeine intake showed a small overall effect when all available domains were pooled (Hedges’ g = 0.24, 95% CI 0.13 to 0.35); however, because these domains represent different constructs, domain-specific estimates were considered the primary interpretable findings. For physical performance, caffeine showed a small favorable effect (g = 0.32, 95% CI 0.22 to 0.42), with statistical evidence for repeated sprint ability (g = 0.43), agility or change in direction (g = 0.42), sprint or speed performance (g = 0.39), anaerobic power (g = 0.30), and jumping performance (g = 0.29). For sport-specific performance, the pooled estimate indicated a small favorable effect but did not reach conventional statistical significance (g = 0.36, 95% CI: −0.01 to 0.73). Exploratory sub-indicator analyses, each based on only a few studies, suggested possible favorable directions for sport-specific locomotion or running performance (g = 0.46) and throwing or ball-speed outcomes (g = 0.19), whereas evidence was insufficient for shooting or scoring accuracy. Physiological outcomes were direction-aligned to the value conventionally regarded as favourable for each indicator (i.e., lower heart rate, lactate, and glucose), so that positive values denote the conventionally favourable direction; because the domain aggregates indicators of differing clinical desirability, its pooled value is a descriptive summary only and showed no clear domain-level direction (g = −0.05, 95% CI −0.31 to 0.21). The heart rate submetric showed a statistically detectable difference (g = −0.30), indicating that caffeine increased heart rate, the expected pharmacological response to a stimulant rather than an adverse effect; there were no clear effects on blood lactate or blood glucose. Perceptual responses improved modestly (g = 0.42), largely through reduced rating of perceived exertion (g = 0.35). Cognitive performance, based on only four studies with low degrees of freedom and wide uncertainty, showed a nonsignificant direction (g = 0.37) with no clear evidence for reaction time or cognitive accuracy, and these data should not be interpreted as showing that caffeine improves cognitive performance in female team-sport athletes. Exploratory moderator analyses did not provide statistically reliable evidence of moderation by caffeine dose, timing of intake, formulation or source, sport type, competitive level, habitual caffeine intake, or blinding status. Conclusions: Available evidence most consistently supports small, outcome-specific benefits of acute caffeine for physical performance and reduced perceived exertion. Evidence for sport-specific skills and cognitive outcomes remained uncertain, based on few studies per outcome and not supporting a general benefit. Current data do not support dose-, timing-, formulation-, habitual-intake-, sport-, or population-stratified recommendations. Future trials should be adequately powered, prospectively report menstrual-cycle phase, hormonal-contraceptive use, habitual caffeine intake, and adverse symptoms, and verify the integrity of blinding. Full article

Background: Falls in older adults are a major public health and rehabilitation concern and may reflect interacting chronic disease-related mechanisms rather than diagnostic labels alone. Type 2 diabetes mellitus (T2DM), hypertension (HTN), and osteoarthritis (OA) are common in later life and may influence fall vulnerability through sensory, vascular, musculoskeletal, cognitive, medication-related, and functional pathways. This scoping review aimed to map mechanism-oriented evidence linking T2DM, HTN, and OA to falls and fall-related outcomes in older adults. Methods: A scoping review was conducted in accordance with established scoping review methodology and PRISMA-ScR guidance. PubMed, Web of Science, and Embase were searched for English-language studies published from 2016 to 2026; the final search was conducted on 15 April 2026. Evidence was charted in a structured table and synthesised descriptively and thematically across disease-specific and shared mechanism domains. Results: A total of 151 studies were included. The evidence was organised into T2DM-related sensory-neural, gait and balance, vestibular/visual-cognitive, strength-related, and glycaemic or medication-related mechanisms; HTN-related haemodynamic, cerebral perfusion, dizziness/syncope, and medication-related mechanisms; and OA-related pain, proprioceptive, strength-related, gait and balance, psychological, and compensatory-control mechanisms. Shared pathways included frailty, multimorbidity, polypharmacy, pain burden, cognitive impairment, sleep disturbance, ADL decline, dizziness, and reduced physical function. Conclusions: Falls in older adults with T2DM, HTN, OA, or multimorbidity may be better understood through interacting disease-specific and shared mechanisms than through diagnostic labels alone. Future longitudinal and multimorbidity-specific studies using standardised fall ascertainment are needed to test these pathways more directly. Full article

University students are frequently exposed to high cognitive demands, which can lead to sustained cognitive load and mental fatigue and may negatively affect learning outcomes and well-being. Electroencephalography (EEG) provides a non-invasive, real-time window into neural activity associated with cognitive effort. This systematic review aims to synthesize current evidence on EEG markers of cognitive load and mental fatigue in university students. The review was conducted in accordance with the PRISMA 2020 statement, and electronic databases including PubMed, Scopus, and Web of Science were systematically searched for peer-reviewed studies on EEG-based assessment of cognitive load and mental fatigue in healthy university students. Seven studies met the inclusion criteria, comprising 179 participants. Cognitive load was most often reflected in changes in theta, alpha, and beta power, as well as band ratios such as theta/alpha. Studies manipulating multimedia design principles generally reported lower cognitive load indicators and better learning performance when these principles were applied. EEG-based markers, particularly theta and posterior alpha activity, show promising potential for monitoring cognitive strain in educational settings; however, methodological variability and small sample sizes limit generalizability. Full article

Background: Corticospinal plasticity is impaired in MS. In-phase bilateral upper-limb exercises have been shown to improve corticospinal excitability in people with relapsing-remitting multiple sclerosis, but there is limited literature that supports the same conclusion for progressive multiple sclerosis. Therefore, our aim was to investigate whether a 12-week in-phase bilateral upper-limb exercise protocol could enhance corticospinal plasticity and improve clinical outcomes in people with progressive multiple sclerosis. Methods: Five participants (two females; age = 61 ± 12.04 years) with secondary or primary progressive multiple sclerosis were randomized and recruited in a single-case concurrent multiple-baseline design study. The exercise protocol lasted for 12 consecutive weeks (30–60 min/session × 3 sessions/week) and incorporated adapted sport-specific activities, functional training and proprioceptive neuromuscular facilitation exercises. To define the functional relationship between the intervention and the results, a visual analysis was conducted. A statistical analysis was performed when a potential sizeable effect was observed. Results: Statistically significant reductions in active motor threshold (primary outcome) were observed in two of the five participants for the left upper limb and in one of the five participants for the right upper limb. Statistically significant improvements were partially observed in muscle strength, pinch strength and cognitive processing speed. Conclusions: Based on the preliminary findings of the current study, in-phase bilateral upper-limb exercises may modulate corticospinal plasticity and improve clinical outcomes in people with progressive multiple sclerosis. However, larger studies are needed to reproduce these results and to establish the effects of in-phase bilateral exercise on both corticospinal plasticity and related clinical outcomes. Full article

Objectives: The aim of this study was to evaluate whether dietary intake-guided precision nutrition interventions, derived from AI-driven food intake monitoring, improve cognitive function and electroencephalographic (EEG) biomarkers in older adults receiving long-term care. Methods: A total of 108 adults aged ≥50 years were recruited from five long-term care facilities. The study included 4 weeks of AI-driven dietary data collection, 2 weeks of data analysis and participant grouping, and 4 weeks of targeted nutritional intervention. Dietary intake was assessed using an AI-based food scanner. Anthropometric measures, biochemical markers, nutritional and cognitive questionnaires, and EEG were evaluated at baseline and postintervention. Participants were classified into three groups based on nutrient intake: “severely inadequate,” “marginally inadequate,” and “adequate.” Tailored food-based interventions, including nut mixes, senior-friendly meat products, and oral nutritional supplements, were provided according to group classification. Results: Energy intake increased in all groups. Nutritional status and cognitive function improved primarily in the severely inadequate group, while favorable EEG changes were observed across all groups. Changes in dietary composition and lipid profiles were observed in the “adequate” group, whereas the “marginally inadequate” group showed no significant changes. Conclusions: AI-based monitoring and nutritional intervention may improve nutritional status, cognitive-related outcomes, and EEG biomarkers in older adults receiving long-term care, supporting the potential of precision nutrition approaches in this population. Clinical Trial Registration KCT0009558 (CRIS, Republic of Korea). Full article

Background: Legal capacity assessment requires multidisciplinary evaluation integrating cognitive, functional, neurological, psychiatric, and medico-legal information. Although large language models (LLMs) have shown promise in structured clinical reasoning, their role in supporting legal capacity assessment remains unclear. This study evaluated the performance of LLMs as AI-assisted decision-support tools using standardized medico-legal case vignettes, with interdisciplinary medical board (IMBD) recommendations under the Turkish Civil Code (TCC) as the expert medical reference standard; IMBD recommendations constitute an expert medical reference standard rather than final judicial determinations. Methods: We retrospectively analyzed 234 court-referred adult cases (2018–2024). Standardized, anonymized medico-legal case vignettes were independently evaluated by ChatGPT-5.2, Gemini 3 Pro, and Claude 4.5 Sonnet. Model outputs were compared with IMBD recommendations. The models were evaluated as AI-assisted decision-support tools and did not replace or influence clinical or judicial decision-making. Performance was assessed using accuracy, macro-F1, Cohen’s κ, AUC, calibration, decision-curve analysis, test–retest reliability, and human-factor outcomes; probability-based metrics were derived from secondary logistic models fitted to the categorical model outputs. Results: Article 405 was the most frequent outcome (65.8%). Dementia increased the likelihood of Article 405 recommendations (OR 6.5, 95% CI 1.2–35.2; p = 0.029), whereas higher Activities of Daily Living scores were protective (OR 0.96; p = 0.004). Gemini 3 Pro achieved the highest accuracy (86.3%), while ChatGPT-5.2 achieved the highest macro-F1 score (0.79) and AUC (0.91). Agreement with IMBD recommendations ranged from κ = 0.60 to 0.73, with high temporal stability (κ = 0.87–0.95); pairwise differences between the three models were not statistically significant after Holm correction. Performance was highest for cases in which Article 405 was recommended and for cases in which no guardianship was recommended, but remained limited for Article 408 (29.6% accuracy). The mean System Usability Scale score was 72.4, and safety flags were identified in 4 of 234 cases (1.7% of cases, corresponding to 4 of 702 individual model outputs). Conclusions: LLMs demonstrated agreement with IMBD recommendations on standardized medico-legal case vignettes, supporting further investigation of their potential role as AI-assisted decision-support tools under expert supervision. Because errors in this domain can directly affect fundamental rights, the use of AI in the legal system and in sensitive medical fields carries substantial risks and must remain strictly limited to expert-supervised decision support. Further prospective studies are needed to evaluate their safe integration into medico-legal practice. Full article

Anthropomorphism has shown inconsistent effects on human judgment, yet the underlying cognitive mechanisms remain underspecified. This research develops and tests a Dual-Pathway Calibration Model (DPCM) integrating dual-process theory, construal level theory, metacognition theory, and regulatory focus theory to explain how anthropomorphic cues influence cognitive processing in human–artificial intelligence (AI) interaction. Three experiments (N = 832) manipulated anthropomorphism and cue inconsistency, examining metacognitive calibration, regulatory focus, and perceived autonomy as boundary conditions. Results revealed that anthropomorphism activates two parallel pathways: (1) a Social Closeness Pathway engaging System 1 processing through reduced psychological distance and enhanced affective trust (indirect effect = 0.18, 95% CI [0.13, 0.24]) and (2) a Cognitive Evaluation Pathway triggering System 2 processing through perceived uncertainty when cue inconsistency is present (ηp² = 0.06). Metacognitive calibration moderated the AI-reliance–decision-quality relationship (β = 0.17, p = 0.007). Regulatory focus moderated pathway activation, with promotion focus strengthening Pathway A (ηp² = 0.15) and prevention focus strengthening Pathway B (ηp² = 0.05). Anthropomorphism exhibited an inverted U-shaped relationship with decision outcomes (quadratic b = −0.05, p = 0.001). These findings extend dual-process theory by specifying conditions triggering intuitive versus analytical processing of anthropomorphic agents, contribute to metacognition theory by demonstrating calibration as a critical determinant of AI-assisted judgment quality, and advance regulatory focus theory by showing motivational orientation shapes social cue processing from artificial agents. Full article

Background/Objectives: Sleep disturbances are increasingly implicated in age-related cognitive decline and may contribute to heterogeneity in cognitive and social–cognitive functioning in Mild Cognitive Impairment (MCI). Nevertheless, it remains unclear whether longitudinal actigraphy-derived sleep parameters predict social cognition, including theory of mind (ToM), across amnestic (aMCI) and non-amnestic (naMCI) MCI subtypes. This study examined longitudinal trajectories of cognitive control and ToM in individuals with aMCI and naMCI and healthy older adults, and investigated whether actigraphy-derived sleep indices prospectively predict subsequent cognitive control and higher-order social cognition across these groups. Methods: A total of 179 participants (46 healthy controls, 75 aMCI, 58 naMCI) were assessed across three waves over approximately 16–20 months. Actigraphy-derived sleep indices were obtained using wrist actigraphy. Cognitive control was assessed with Delis–Kaplan Executive Function System subtests, whereas ToM was evaluated through tasks involving non-literal language comprehension, metaphor and proverb interpretation, higher-order mentalizing, and emotion recognition. Longitudinal trajectories were examined using mixed-design ANOVAs, and prospective sleep effects were tested using longitudinal path models. Results: Both cognitive control and ToM declined over time in the MCI groups, whereas healthy controls showed relative stability. Subtype differences in cognitive control emerged primarily in higher-order planning and rule-monitoring processes, with naMCI showing greater impairment. ToM revealed a clearer and more consistent gradient (healthy controls > aMCI > naMCI), particularly in higher-order inferential tasks. Among the actigraphy-derived sleep indices, only TST prospectively predicted later ToM performance, whereas prospective associations with cognitive control were limited and inconsistent. Conclusions: Reduced sleep duration was prospectively associated with poorer subsequent performance in higher-order social cognition, independently of the executive-control measures examined. These findings highlight phenotypic heterogeneity across MCI subtypes and suggest that objectively measured sleep duration may serve as a clinically relevant longitudinal marker of social–cognitive vulnerability. Future studies are needed to determine whether interventions targeting sleep duration are associated with improved social–cognitive outcomes. Full article

Perioperative stress induces profound molecular and cellular responses that contribute to postoperative complications, including perioperative neurocognitive disorders (PND), chronic postsurgical pain, organ dysfunction, immunothrombosis, fibrosis, and cancer progression. Increasing evidence demonstrates that epigenetic mechanisms act as central regulators linking surgical trauma, inflammation, metabolic stress, ischemia–reperfusion injury, and immune activation to long-term alterations in gene expression and tissue remodeling. DNA methylation, histone modifications, chromatin remodeling, non-coding RNAs, and RNA epitranscriptomic mechanisms such as N6-methyladenosine (m6A) collectively orchestrate perioperative responses across multiple organ systems. Recent translational studies have identified histone deacetylases (HDACs), histone methyltransferases, NETosis-associated chromatin signaling, HMGB1/NF-κB activation, and epigenetic regulation of neuroimmune pathways as major contributors to postoperative cognitive dysfunction, chronic pain, cardiac dysfunction, pulmonary injury, and fibrosis. In parallel, advances in liquid biopsy, circulating tumor DNA (ctDNA), and single-cell epigenomics have opened new opportunities for biomarker-guided perioperative precision medicine. This review summarizes current evidence regarding epigenetic regulation in perioperative medicine with special emphasis on neuroepigenetics, NETosis, fibrosis, cardiac epigenetics, immune remodeling, and perioperative oncological outcomes. Furthermore, we discuss emerging therapeutic strategies targeting HDACs, DNA methylation, m6A pathways, and chromatin-associated inflammatory signaling as potential future interventions for perioperative complications. Full article

Cognitive processes such as executive function are associated with positive behavioral and health outcomes across the lifespan, highlighting the importance of identifying early predictors of executive functioning. During infancy and early childhood, the development of motor skills provides opportunities for action, exploration, and learning that may support emerging cognitive processes. The present exploratory study examined the relation between fine motor skills and executive function in 2-year-old children (N = 33; 13 girls and 20 boys; M = 31 months; age range = 25–35 months). Participants completed the fine motor subtests of the Peabody Developmental Motor Scales, assessing grasping and visual motor integration, and the Minnesota Executive Function Scale as a measure of executive functioning. Fine motor skills were positively associated with executive functioning; however, when controlling for age, only visual motor integration remained significantly correlated with executive functioning. A multiple linear regression analysis revealed that both grasping and visual motor integration significantly predicted executive functioning after controlling for age. These findings suggest that fine motor skills, especially the coordination of visual and manual processes, may play an important role in early executive function development independent of age. Interventions that support fine motor development may therefore have the potential to confer broader benefits for executive functioning in toddlers. Full article

Rapid technological advancements are transforming educational practice and reshaping the traditional conception of learning. In particular, immersive technologies, such as augmented reality (AR) and virtual reality (VR), have shifted the focus from learning outcomes alone to the quality of the learning environment and the psychological processes involved in learning (e.g., motivation and cognitive processes). Against this background, the current perspective proposes a reconceptualization of immersive technologies (virtual reality, augmented reality, and mixed reality) as ecological learning environments. Specifically, by integrating the neo-ecological framework with the Cognitive-Affective Model of Immersive Learning (CAMIL), we argue that immersive technologies create hybrid physical–virtual microsystems in which embodied and experiential learning emerge as pedagogical processes through which knowledge is actively constructed. From this perspective, learning results from the interaction between ecological contexts, immersive psychological mechanisms, and learners’ active engagement with the environment. We further discuss the important limitations and ethical challenges associated with immersive technologies. Finally, we suggest that immersive technology should be integrated into blended educational approaches consisting of traditional learning combined with immersive technologies. Full article

Background/Objectives: Postural control depends on the integration and reweighting of visual, somatosensory, vestibular, and contextual sensory information. Stable auditory cues may support balance, whereas complex musical stimulation may impose additional sensory-cognitive demand during multisensory conflict. This study examined the acute effects of relative device-output music intensity on virtual-reality-based postural control in trained athletes and explored whether responses differed by sport background. Methods: Forty-eight athletes from tennis, combat sports, swimming, football, and volleyball completed the Clinical Test of Sensory Interaction in Balance delivered through virtual reality (CTSIB-VR) and Limits of Stability (LOS) assessments under four auditory conditions: routine/no sound and low (+10 dB), moderate (+20 dB), and high (+30 dB) relative device-output increments. Linear mixed-effects models included sport, auditory condition, and their interaction as fixed effects and participant-specific random intercepts and random linear condition slopes. Model-based estimated marginal means, Bonferroni-adjusted contrasts, 1.5×IQR sensitivity analyses, and robust generalized estimating equations were calculated. Results: Auditory condition affected all five CTSIB-VR outcomes (Wald χ²(3) = 16.773–94.404, all p < 0.001). The routine condition exceeded the high-intensity condition for composite score (adjusted mean difference = 6.05, 95% CI 3.99–8.10; Bonferroni-adjusted p < 0.001) and somatosensory score (8.62, 95% CI 6.78–10.46; adjusted p < 0.001). Sport × condition interactions were significant for all CTSIB-VR outcomes (χ²(12) = 54.869–98.953, all p < 0.001), but sport-stratified findings were exploratory. For LOS, auditory-condition effects were detected for endpoint excursion (p = 0.004), maximum excursion (p < 0.001), and directional control (p = 0.002), whereas reaction time (p = 0.648) and movement velocity (p = 0.056) did not show clear main effects. Sensitivity analyses supported the endpoint-excursion, maximum-excursion, and directional-control findings; movement-velocity inference was method-sensitive. Conclusions: Relative device-output music intensity was associated with consistent changes in CTSIB-VR sensory-organization measures and outcome-specific changes in LOS performance. Sport-related patterns require confirmation in adequately powered, balanced samples. Full article

Generative artificial intelligence is increasingly used in higher education to provide explanations, solutions, feedback, and organizational support. Although current debates emphasize academic integrity, productivity, and instructional innovation, less attention has been given to how the timing and form of AI assistance may affect learning after that assistance is removed. This conceptual paper develops the Retrieval Interruption Framework (RIF) through a targeted narrative synthesis of research on retrieval practice, productive failure, scaffolding, cognitive load, cognitive offloading, metacognitive monitoring, the expertise reversal effect, the assistance dilemma, and AI-assisted learning. RIF is proposed as an integrative, AI-specific framework rather than a distinct theory of cognition. It distinguishes retrieval-preserving assistance from retrieval-displacing assistance. Retrieval-preserving assistance supports learners after they have attempted task-relevant recall, self-explanation, problem representation, or solution generation. Retrieval-displacing assistance supplies the targeted explanation, solution, or reasoning structure before an initial learner response. The framework predicts that retrieval-displacing assistance may improve immediate performance while weakening delayed unsupported recall, explanation quality, transfer, or metacognitive calibration, particularly in conceptually demanding tasks and among learners with limited prior knowledge. However, early AI guidance may remain productive when it reduces extraneous cognitive load, promotes active processing, fades over time, and is followed by independent performance. RIF reframes AI integration as a sequencing and instructional-design problem. Future research should compare specific forms of AI-first and learner-first assistance using immediate performance measures and delayed unsupported learning outcomes. Full article