Search Results (241)

This study examined whether adults with varying levels of dyslexia-related risk show distinct profiles of academic anxiety and working memory functioning. Dyslexia-related risk was assessed with the corrected Chinese Adult Reading History Questionnaire (Chinese-ARHQ). Latent profile analysis was conducted using reading anxiety, mathematics anxiety, a digit-span working memory composite, and operation span as profile indicators. Corrected Chinese-ARHQ scores were then compared across the retained profiles as an external variable, and a sensitivity analysis was conducted in the elevated dyslexia-related risk subsample defined by Chinese-ARHQ scores above 0.36. A four-profile solution was retained: Low Anxiety-Average Cognition, High Anxiety-High Cognition, Very Low Verbal Working Memory, and High Anxiety-Low Cognition. The coexistence of high-anxiety profiles with different levels of cognitive performance suggests that, within the specific profile distribution of this sample, elevated academic anxiety was not consistently accompanied by uniformly lower working memory performance. Corrected Chinese-ARHQ scores did not differ significantly across profiles, suggesting that the identified emotion-cognition patterns were not closely aligned with retrospective reading-difficulty severity in this sample. Overall, the findings provide preliminary evidence that current academic anxiety and working memory performance may form distinguishable configurations among adults with varying dyslexia-related risk, while also highlighting the need for replication with independent and clinically characterized samples. Full article

Brain–computer interface (BCI) systems aim to establish direct communication pathways between neural activity and external devices, enabling interaction without relying on conventional neuromuscular mechanisms. This study investigates the feasibility of decoding binary decisions (“Yes”/”No”) from self-generated cognitive–emotional modulation patterns using a single-channel low-cost EEG device. The proposed approach evaluates whether internally generated modulation strategies can produce distinguishable neural activity suitable for BCI applications under constrained acquisition conditions. EEG signals were recorded from two participants using a consumer-grade headset while they responded to questions through intentional internal modulation associated with affirmative and negative responses. The recorded signals were preprocessed, and multiple feature representations were extracted, including raw temporal data, cepstral coefficients, spectral power, and continuous wavelet transform (CWT) features. Several machine learning and deep learning models, including convolutional neural networks (CNN), long short-term memory networks (LSTM), and support vector machines (SVM), were trained and evaluated using hold-out and stratified k-fold validation strategies. The best performance was achieved by a CWT-based CNN model, reaching an average accuracy of 80.5%, significantly above chance level. Additional models, including CEP-CNN and RAW-LSTM, achieved competitive results, highlighting the relevance of feature representation in EEG-based classification tasks. The results demonstrate that internally generated modulation patterns can produce distinguishable EEG responses, even when using low-cost single-channel hardware. Although the limited number of participants constrains statistical generalization, this work serves as a proof-of-concept and provides a reproducible experimental pipeline for future studies. Overall, the findings support the development of accessible, scalable, and user-centered BCI systems based on internally generated neural modulation strategies, contributing to more natural interaction paradigms in EEG-based communication systems. Full article

Background/Objectives: Children with single-sided deafness (SSD) have normal hearing in one ear and are deaf in the other. Navigating complex auditory environments with SSD may cause reallocation of cognitive resources necessary for executive functioning (EF), adding potential cognitive burden to listening, though this is not well understood. To characterize EF in children with SSD, we compared their test performance and everyday functioning on performance-based and caregiver-rated EF measures to normative values and to a group of children with temporal lobe epilepsy (TLE). Methods: A retrospective review compared children with unaided SSD (n = 45) to a clinically referred TLE group (n = 39), all aged 6–16 years old, on performance-based measures including verbal fluency (letter, category), digit span, coding, and the BRIEF general executive composite. In the SSD group, those with congenital and acquired onset were compared across the same performance-based measures and BASC-3 executive functioning composite, and BRIEF2 indexes (cognitive, emotional, and behavioral regulation). Within this SSD group, performance-based and caregiver-rated measures were correlated. Results: In the SSD group, caregiver-reported EF and test performance were within age expectations. However, SSD participants with congenital onset had poorer caregiver-reported everyday EF. Children with SSD and elevated caregiver-reported EF had greater challenges on performance measures of auditory working memory. EF profiles were similar in the SSD and TLE groups, except the TLE group showed significantly worse performance on semantic fluency. Conclusions: Caregiver-rated EF measures may serve as an important tool for detecting neuropsychological deficits in children with SSD. SSD children with congenital onset may benefit from closer EF monitoring. There was lower performance on digit span backward tasks that require auditory working memory in children with elevated daily EF. More research is needed to determine what factors, such as hearing technology use, contribute to EF in children with SSD. *The term SSD is used throughout this article as a neutral placeholder with respect to the variation of terms used with this population (e.g., deaf, hard of hearing, hearing loss, hearing differences, etc.). SSD is used to be inclusive of all cultural/medical perspectives and identities. Full article

Trauma-related autobiographical memories can manifest as involuntary, vivid, emotionally charged intrusions that perpetuate avoidance, negative emotions, and functional impairment. While these memories are central to post-traumatic stress disorder (PTSD), they also occur across diagnoses and are often reported in depressive disorders, including treatment-resistant depression (TRD). Although trauma-focused psychotherapies are effective, their routine implementation can be limited by dropout, residual symptoms, and difficulty engaging patients with severe depression, dissociation, or complex comorbidities. Intranasal esketamine is an approved rapid-acting treatment for TRD and has been hypothesized to create transient conditions that may facilitate psychotherapeutic work on traumatic memories. This narrative review synthesizes clinical and translational evidence on ketamine and esketamine for PTSD and trauma-related symptoms, with particular attention to the distinction between intravenous ketamine studies, intranasal esketamine data, and studies combining these compounds with psychotherapy. Currently, the most robust evidence in this area comes from three randomised trials of intravenous ketamine for PTSD. In contrast, data on intranasal esketamine and psychotherapy-combination approaches are mainly from pilot studies, retrospective analyses, or case reports. We additionally propose a pragmatic, feasibility-oriented protocol integrating intranasal esketamine with a structured traumatic-memory intervention for TRD patients with clinically relevant trauma-memory symptoms. The novelty of the proposal does not lie in claiming efficacy, but in specifying a standardised imagery rescripting module and predefining two timing hypotheses. The proposal targets patients with TRD with relevant trauma-memory symptoms, and it embeds the intervention within existing esketamine-care infrastructure. Overall, the available literature supports mechanistic plausibility and preliminary feasibility more than clinical efficacy. The evidence base remains small, heterogeneous, and largely uncontrolled, and controlled studies are needed before efficacy claims can be made. Full article

Daylight Saving Time (DST) creates abrupt, externally imposed circadian disruptions that can impair sleep regulation, hormonal balance, cognitive performance, and emotional stability. Although these effects are known in the general population, individuals with chronic mental illness, whose circadian systems are often intrinsically dysregulated, may face increased neuropsychological consequences. This comprehensive review synthesizes evidence from chronobiology, psychiatry, neuroscience, and population health to examine how DST-related circadian misalignment impacts cognitive functioning, mood regulation, suicidality risk, and symptom exacerbation across psychological disorders such as depression, anxiety disorders, bipolar disorder, post-traumatic stress disorder, attention-deficit/hyperactivity disorder, and psychotic disorders. Following the Scale for the Assessment of Narrative Review Articles (SANRA) guidelines, a search of PubMed, PsycINFO, Scopus, and Google Scholar was conducted to identify studies published from 2000–2026 examining DST, circadian rhythm disruption, neuropsychological outcomes, and chronic mental illness. Empirical, theoretical, and mechanistic studies were included to ensure comprehensive synthesis. Across conditions, DST, particularly spring forward transitions, is associated with increased sleep disturbance, impaired executive functioning, reduced attention and working memory, heightened emotional reactivity, increased depressive symptoms, elevated risk of manic episodes, and short-term increases in suicidality. Neurobiological mechanisms include altered melatonin secretion, cortisol dysregulation, Hypothalamus Pituitary Axis (HPA-axis) activation, and clock-gene desynchrony. DST may function as a modifiable negative environmental influence capable of affecting neuropsychological functioning in vulnerable populations. These findings underscore the need for clinical awareness, preventive strategies, and policy reconsiderations, including calls to eliminate seasonal time changes. Standardizing DST-related research outcomes and expanding longitudinal, multi-site studies will be essential for advancing this emerging field. Full article

Empathetic dialogue systems built upon large language models overwhelmingly adopt a monolithic inference paradigm that processes emotion perception, causal reasoning, memory retrieval, and response planning within a single forward pass without architecturally enforced intermediate representations, forfeiting intermediate-state transparency and long-horizon personalization. Drawing on neuroscientific and cognitive–psychological evidence that human empathy is functionally dissociable, we present MOSAIC (Multi-agent Orchestration with Structured Affective memory for Interpretable empathiC dialogue), a training-free framework that operationalizes empathetic dialogue as a four-stage cognitive pipeline: affective perception, causal appraisal, episodic memory retrieval, and response synthesis. Three innovations distinguish MOSAIC from prior work: (1) a cognitively motivated modular architecture whose functionally dissociable stages enable post hoc failure attribution through logged intermediate states; (2) a hierarchical three-tier emotional memory—perceptual, semantic, and episodic—coupled with adaptive three-dimensional retrieval over emotion, situation, and coping-strategy cues; and (3) a heterogeneous model orchestration strategy coordinating open-source and API-accessible models through role-specific chain-of-thought prompts, requiring no task-specific fine-tuning. We note that the EmpatheticDialogues evaluation pre-populates the memory store with 200 training-split episodes prior to test-set interaction, a data-access asymmetry relative to single-model baselines that must be borne in mind when interpreting comparative results. Experiments on EmpatheticDialogues and ESConv show that MOSAIC achieves a 76.4% weighted F1 and an empathy score of 3.87 (on a 1–5 Likert scale) and that it improves over single-model, training-free baselines on aggregate empathy and—most prominently—on human-rated personalization (3.67 vs. 3.24 against Claude-3.5 five-shot, $d=0.48$). We caution that the comparison against training-free baselines is not data access-controlled (see the cold-start discussion in Methods); the personalization advantage, supported by the ablation without the Event Agent, is the result we treat as the primary practical contribution of this work. Full article

Background: Posttraumatic stress disorder (PTSD) in ages 3–18 is associated with disturbances in attention, working memory, processing speed, and executive control, as well as persistent difficulties in affect regulation. These neuropsychological vulnerabilities might interfere with learning, peer relationships, and the consolidation of age-appropriate developmental skills. Methods: We conducted a narrative review informed by a structured literature search in PubMed, Scopus, PsycINFO, Embase, EBSCOhost, Web of Science, and Google Scholar. English-language publications from 1990 to 2025 were considered if they examined (1) neuropsychological outcomes of trauma exposure or PTSD in youth and/or (2) interventions with potential to modify neurocognitive or affective functioning, including trauma-focused cognitive behavioral therapy (TF-CBT), mindfulness-based interventions, cognitive rehabilitation strategies, and biofeedback/neurofeedback. Results: Across study designs, trauma exposure and PTSD in youth are consistently linked to impairments in attentional control and executive functioning, with downstream effects on everyday memory and academic performance. Neurobiological studies commonly implicate altered reactivity within amygdala-centered threat circuits and reduced top-down modulation by prefrontal networks, although findings vary with trauma type, developmental stage, and comorbidity. TF-CBT remains the best-supported intervention for pediatric PTSD symptoms; however, neurocognitive outcomes are measured less frequently. Mindfulness-based programs show promise for strengthening attention and emotion regulation when carefully adapted for trauma-exposed youth. Neurofeedback and targeted cognitive rehabilitation represent emerging approaches with preliminary evidence, but the literature remains heterogeneous. Conclusions: An intervention strategy that combines symptom-focused trauma therapy with explicit targeting of executive control, memory processes, and affect regulation may represent a developmentally informed clinical framework for trauma-exposed youth. Future trials need to incorporate standardized neuropsychological endpoints and examine moderators that inform treatment matching. Full article

Transcranial electrical stimulation (tES) has been widely investigated for cognitive enhancement and neurorehabilitation; however, its cognitive effects remain highly variable across studies and individuals. Increasing evidence suggests that this variability may be explained by state-dependent and history-dependent plasticity mechanisms rather than stimulation parameters alone. This systematic review aimed to synthesize experimental human studies investigating how stimulation protocols interact with brain state, baseline performance, and prior stimulation history to influence cognitive outcomes. Following PRISMA 2020 guidelines, systematic searches were conducted in PubMed, Scopus, and Web of Science, resulting in 27 eligible experimental studies published between 2008 and 2024. Across cognitive domains such as working memory, declarative memory, perceptual learning, inhibitory control, and creativity, stimulation effects were consistently modulated by baseline performance, task engagement, emotional or physiological state, stimulation timing, and prior stimulation exposure. These findings suggest that transcranial electrical stimulation may be better conceptualized as a state-dependent modulator of neural plasticity rather than a direct cognitive enhancement technique. Overall, the review indicates that protocol-dependent factors such as timing, priming, baseline state, and stimulation history play a critical role in shaping cognitive outcomes. Future research should therefore prioritize state-dependent, task-coupled, and individualized stimulation protocols to improve reproducibility and to better understand variability in cognitive and clinical outcomes. Full article

In this study, we examined how disinformation and trustworthy news differ in their narrative construction across nine theoretically motivated dimensions. We address the following research question: how do disinformation and trustworthy news differ in narrative organisation and epistemic grounding? We analysed 610 English-language news articles (308 pro-Kremlin disinformation and 302 trustworthy articles) covering selected international events from 2015 to 2023, using data derived from the EUvsDisinfo dataset. Narrative elements were extracted using a hybrid pipeline combining large language models and knowledge graphs, resulting in article-level representations for comparative analysis. Ordinal scores (1–5) were assigned for emotional intensity, cultural complexity, conspiracist structure, source diversity, crisis intensity, evidence support, media control, solutions orientation and memory work. Non-parametric comparisons showed significant differences in eight of these nine dimensions. Disinformation articles revealed stronger conspiracist structuring and greater meta-media hostility, as well as significantly lower source diversity, evidence support, cultural complexity and weaker memory work. Emotional intensity did not differ reliably across disinformation and trustworthy news. A simple additive NarrativeRisk score, which we designed as a transparent and interpretable summary measure, showed between-group differences in both parametric and non-parametric tests. As a univariate discrimination indicator, NarrativeRisk achieved ROC AUC ≈ 0.84. Cluster analysis identified three recurrent narrative profiles, including one dominated by disinformation, one by trustworthy news and one mixed profile. These findings indicate that disinformation is distinguished not only by factual unreliability but also by different patterns in narrative organisation. Full article

The increasing prevalence of work-related stress requires advanced, non-intrusive physiological monitoring solutions. As conventional methods are often impractical for continuous, real-world applications, this study investigates the deployment of artificial intelligence models on embedded systems for real-time emotion recognition from physiological signals. The study identified critical constraints for embedded implementation, including model size and memory capacity. An evaluation of various machine learning algorithms revealed that, while models like K-Nearest Neighbors (KNN) achieve high accuracy (88.8%), their excessive memory footprints make them unsuitable for resource-constrained hardware. Consequently, Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and recurrent neural network (RNN) architectures were deployed on an STM32F411 microcontroller, for which model compression proved essential. An experimental study validated the approach, achieving high recognition rates for pronounced emotions such as hatred (91%) and anger (85%), though with a lower accuracy for more subtle states. These results confirm the potential of embedded AI systems for physiological monitoring, highlighting the critical importance of feature selection and model compression for practical implementation. Full article

Background/Objectives: Cognitive dysfunction, or “brain fog”, following COVID-19 viral infection is strongly associated with diminished work capacity which disproportionality affects working-age adults. This study examined an existing method of cognitive rehabilitation training applied to adults struggling with workplace functioning and self-efficacy due to post-COVID-19 brain fog. Methods: Nine adults with post-COVID-19 cognitive dysfunction participated in this single arm pilot trial of a severity-adaptive cognitive training program. The participants completed 45–90 h of clinician-delivered cognitive training exercises delivered remotely in 60- to 90-min sessions, two or three times per week. The primary outcome measure was overall workplace self-efficacy with subskills of perceived workplace functioning, perception of cognitive functioning, and perception of home functioning assessed through pre and post surveys and qualitative interviews. The secondary outcome was cognitive function operationalized by an IQ score administered before and after the intervention. Results: The participants achieved significant improvements in workplace self-efficacy and cognition following cognitive training. The main qualitative themes of self-reported improvements were in executive function, health and energy, daily living activities, productivity, and socioemotional functioning. A cross-case synthesis of pre-intervention struggles, and post-intervention improvements revealed subthemes at work or school in cognitive processing and comprehension, memory, executive function, fatigue, emotional distress, confidence in work or academics, and work/academic performance impairment. As a group, the mean gain in IQ score was 10.5 points. Conclusions: This study adds to the growing body of literature examining the possibility of using cognitive rehabilitation for post-COVID-19 cognitive dysfunction impacting workplace self-efficacy and work functioning. Full article

This article examines the resurgence of a series of diverse practices from mending and sewing, to embroidery, knitting and crochet, which are traditionally situated in broader debates about gender and domestic labor but also care work, everyday life, and sustainability. While recently reframed as feminist and eco-conscious practices, these crafts have only been partially explored in their material, symbolic, and emotional aspects due to their association with the feminine and domestic sphere, their invisibility within public discourse, and the stigma attached to repair in consumer capitalist societies. Drawing on an ethnographic study conducted between 2023 and 2025, the research examines the intergenerational transmission of these skills within eleven Italian families. Semi-structured dyadic interviews were carried out with at least two members of each family, predominantly women, exploring learning processes, everyday uses, emotional meaning, and their influence on clothing consumption. Findings reveal a complex and discontinuous trajectory of transmission, shaped by gender expectations, class dynamics, and shifting cultural meanings: while older generations often learned these crafts out of necessity and social obligation, younger generations approach them as creative hobbies, tools for self-expression, or forms of sustainable consumption. Across generations, however, the crafts emerge as powerful affective languages through which care, memory, and relational bonds are materialized in clothing. Full article

Background: The global burden of mental disorders continues to escalate, necessitating scalable, evidence-based interventions. Artificial intelligence (AI)-delivered health promotion programs represent a promising approach to addressing treatment gaps by targeting the neuropsychological mechanisms that underlie mental health outcomes. This meta-analysis synthesizes evidence on the effectiveness of AI-delivered interventions in improving executive function, emotion regulation, and clinical outcomes across diverse populations. Methods: A systematic search identified 186 studies (n = 22,755 participants) published between 2020 and 2025. Random-effects meta-analyses estimated pooled effect sizes (Hedges’ g, calculated as between-group standardized mean differences with small-sample correction [J = 1 − 3/(4df − 1)]) for primary outcomes. Between-study heterogeneity was quantified using I² and τ² statistics. To address dependency among effect sizes from studies reporting multiple outcomes, robust variance estimation (RVE) was employed. Subgroup analyses examined intervention modalities, delivery formats, and clinical populations. Moderator analyses explored sources of heterogeneity, including publication year, sample size, intervention duration, control condition type, risk-of-bias rating, geographic region, and AI sophistication tier, and mediational models tested putative therapeutic mechanisms. Results: AI-delivered interventions demonstrated a significant overall effect on health outcomes (g = 0.68, 95% CI [0.58, 0.78]; τ² = 0.12; I² = 73.4%). Executive function outcomes showed moderate effects (g = 0.61, τ² = 0.08), with working memory improvements being strongest (g = 0.72). Emotion regulation outcomes demonstrated moderate-to-large effects (g = 0.61, 95% CI [0.51, 0.70], τ² = 0.006); formal subgroup pooled estimates by emotion regulation strategy were not calculated due to insufficient studies per strategy (k < 3 per category); individual study effect sizes ranged from g = 0.27 to g = 1.11. Among 41 studies examining neuropsychological mechanisms, convergent patterns suggested involvement of prefrontal neural circuits (DLPFC), enhanced alpha-band activity, and improved heart rate variability; however, formal mediation was tested in only 18 studies (9.7%). Among clinical populations, interventions for cognitive impairment yielded the largest effects (g = 1.02; this finding should be interpreted cautiously given modest cumulative sample size [n = 482], potential small-study effects [Egger’s p = 0.08], and trim-and-fill adjusted estimate of g = 0.85), followed by mental health conditions (g = 0.72), while other clinical populations showed smaller but significant improvements (g = 0.19). Mobile applications (g = 0.78) and chatbot-based interventions (g = 0.74) demonstrated the strongest effects among delivery formats. Among studies testing formal mediation, analyses suggested mindfulness (β = 0.42), decentering (β = 0.38), and cognitive reappraisal (β = 0.45) as processes associated with therapeutic outcomes. Conclusions: AI-delivered health promotion programs demonstrate significant effectiveness across executive function, emotion regulation, and clinical outcomes, though substantial heterogeneity (I² = 45–82%) indicates meaningful variability warranting attention to subgroup-specific effects. Given the diversity of intervention types included (chatbots, mobile apps, VR systems, neuromodulation), pooled estimates should be interpreted as characterizing the average effect across this heterogeneous landscape; subgroup-specific estimates provide more precise guidance for clinical decision-making regarding specific modalities. Effects are associated with convergent patterns of neuropsychological mechanisms, though mechanistic conclusions remain preliminary given that only 22% of studies (41/186) examined neuropsychological mechanisms, and formal mediation analyses were conducted in only 18 studies (9.7%); most of the mechanistic evidence is correlational rather than causal. Future research should establish standardized AI taxonomies, optimize adaptive algorithms, conduct adequately powered replication studies in populations with cognitive impairment, prioritize experimental mediation designs to establish causal pathways, and evaluate long-term maintenance effects with a minimum of 6–12-month follow-up periods. Full article

Background/Objectives: To study the hypothesis that cognitive functions and learning skills are impaired in child/adolescent childhood cancer survivors (CCS). Secondary outcomes included psychosocial parameters and quality of life. Methods: This case–control study was conducted over four years (2017–2021) at the largest pediatric Aghia Sophia Children’s Hospital, in Greece. Eligible participants were children and adolescents in Greece. For CCS, ≥1 year should have elapsed from completion of cancer treatment. Assessments of neurocognitive function, learning and psychosocial skills and health-related quality of life (HRQoL) were performed with validated instruments (WISC-III, LAMDA software, Achenbach CBCL/6-18 and YSR, KIDSCREEN-52, respectively). Results: In total, 219 participants (47.49% males, mean age ± SD 11.72 ± 2.32 years), 70 CCS and 149 controls (matched for age, sex, family income), were included. Cases were CCS of acute lymphoblastic leukemia (n = 25)/brain tumors (n = 19)/lymphoma (n = 17)/nephroblastoma (n = 5)/Ewing sarcoma (n = 3)/rhabdomyosarcoma (n = 1). CCS had worse scores in full-scale Intelligence Quotient (FSIQ) (p = 0.004), verbal IQ (VIQ) (p = 0.005) and all its subscales, performance IQ (PIQ) (p = 0.021), and almost all learning parameters than controls. Attention, working memory, writing/visual–motor coordination, processing accuracy/speed, language acquisition/expression, all psychosocial scales, and HRQoL domains of mood and emotions, were negatively affected in CCS. Female CCS demonstrated lower FSIQ (p = 0.019) and VIQ (p = 0.014) than control females, whereas male CCS retained their total IQ unaffected. Among CCS, those with non-central nervous system (CNS) tumors, higher parental educational level or higher family income had significantly higher IQ than those with CNS tumors, lower parental educational level or lower family income, respectively. Conclusions: CCS in Greece carry a significant burden of cognitive and psychological morbidity. Cognitive/educational and psychosocial support to CCS is imperative. Full article

Black Modernist architecture offers a powerful yet underexamined pathway for advancing restorative capacity in American cities. This paper argues that Black Modernism functions as a restorative design methodology, addressing social, economic, and ecological harm imposed on Black communities through slavery, racial capitalism, urban renewal, and infrastructural violence. Grounded in the restorative economics framework pioneered by O’Hara, the paper explores the role Black Modernism plays in sustaining sink capacities defined as the social, ecological, and emotional processes that absorb stress, pollution, waste, and trauma. Conventional economic models ignore these capacities, despite their necessity for economic productivity. Black communities, like all marginalized communities, have historically been forced to provide them without compensation. Situating Black Modernist architecture within this framework, the paper demonstrates how Black architects have designed buildings and landscapes that restore dignity, memory, health, and cultural identity, thereby expanding community sink capacities. Drawing on the works of various scholars, the paper examines case studies from Washington, DC, Atlanta, and Chicago, which reveal how Black communities have borne the burden of unremunerated restorative labor while shaping the American built environment. The paper positions Black Modernism as both a design language and a political–economic intervention, challenging architectural value systems that privilege monumental production over community restoration. It concludes by proposing a Restorative Design Framework that integrates Black Modernist principles with restorative economics, offering policy and planning pathways that recognize cultural labor, emotional restoration, and community well-being as essential components of sustainable urban development. Full article