Nonverbal behaviours are social tools, used to signal our intentions and feelings to our social partners. Successful communication should therefore depend upon our 'readability': how interpretable these nonverbal signals are. However, while children's ability to reliably interpret their social partners has been well researched, there is a lack of research into the development of readability. To address this gap, 36 typically developing 5- to 11-year-old children were covertly video recorded interacting with a researcher. This captured their naturalistic responses to four different social scenarios. Five-second, silent video clips of each child's reactions to each scenario were created and shown to 27 adult perceivers. These perceivers were then asked to infer which of the four potential scenarios each child was reacting to in each clip, allowing us to measure how 'readable' each child was. Perceivers were further asked to rate how expressive they felt each child was against a five-point Likert scale. This study was pre-registered on the OSF. This is the first study to demonstrate that children between 5 and 11-years-old are readable social actors. Contrary to our expectations, we found no significant effect of age on target readability. On the other hand, target's expressivity was significantly associated with their readability. These results have implications for our understanding of how children become successful communicators and suggest that readability might be a stable trait over this age range - varying between individuals in a similar manner to that previously observed in facial expressivity.

Non-autistic individuals find it difficult to read the behaviour of autistic people in comparison to non-autistic others. We investigated whether non-autistic people's ability to read autistic individuals is improved by providing diagnostic information, and whether this ability is associated with a person's knowledge about autism, prior contact with autistic people, and autism stigma. Participants (N = 128) viewed videos that were taken from a previous study. These showed autistic and non-autistic individuals reacting to events enacted by the researcher, and participants were asked to infer what event had taken place. Videos were presented either with no diagnostic information, a correct diagnostic label, or an incorrect label (autistic individuals labelled as non-autistic and vice versa). Autism knowledge, contact with autistic people, and autism stigma were measured by questionnaires. Participants performed less well for videos of autistic than non-autistic others. Diagnostic information had little impact on performance, although labelling non-autistic individuals as autistic reduced accuracy. Autism knowledge, contact with autistic people, and autism stigma were not associated with relative strength in interpreting the behaviour of autistic individuals. We conclude it might be difficult to train people to read autistic people's non-verbal behaviour more effectively; instead, intervention might focus on raising awareness of this issue.Lay AbstractRecent research has shown that non-autistic people are prone to misinterpreting the behaviour of autistic individuals, which may contribute to the difficulties autistic people often experience during social interactions. This suggests that interventions should identify ways to improve other people's ability to interpret autistic people's behaviour. However, little is known about what circumstances may improve non-autistic people's ability to read autistic others. This study investigated whether telling people that someone is autistic would improve their ability to interpret the behaviour of that person. We also investigated whether having more knowledge about autism, having previous contact with autistic people, or holding stigmatic attitudes about autism relates to this ability. The researchers used video clips that were recorded for a previous study. They showed autistic and non-autistic people reacting to aspects of the researchers' behaviour, such as being told a joke or paid a compliment. Participants' task was to watch the video clips and infer what the person in each video was reacting to and accuracy in doing so was recorded. The videos were presented with either no diagnostic information or with a diagnostic label alongside the video, which was either correct or inaccurate (labelling autistic individuals as non-autistic and vice versa). We used questionnaires to assess participants' autism knowledge, previous contact with autistic people, and autism stigma. We found that participants had more difficulty judging the reactions of autistic individuals than the non-autistic individuals. Telling participants that a person was autistic did not make people better at interpreting their behaviour, although labelling non-autistic participants as autistic reduced accuracy. Knowledge about autism, previous contact with autistic people, and autism stigma did not relate to a person's ability to interpret autistic people's behaviour. This suggests that it may not be easy to create interventions to improve people's ability to interpret the behaviour of autistic others. Intervention might focus on raising awareness of the need to avoid making assumptions based on the non-verbal behaviour of autistic people.

Understanding how early mother-child interactions are linked to children's social-cognitive processes requires methods capable of capturing the temporal structure of naturalistic behavior. This study introduces a computational framework based on Bayesian Network modeling to identify sequential dependencies among nonverbal behaviors (smiles, gaze, and social touch) exchanged during free play in mother-child dyads (n = 38; age 3 years). From each network, we derived the Order of Sequential Interaction (OSI), a compact index of interaction complexity. We then examined its associations with behavioral, physiological, and neural measures relevant to cognitive development. Although OSI was not associated with language or executive-function scores, analyses revealed links between OSI and prosocial behavior, facial EMG, and neural responses (rTPJ, lIFG) during prosocial-scene viewing. These findings suggest that OSI may capture aspects of interaction structure specifically connected to children's social and affective responsiveness. Building on this, the present framework demonstrates how probabilistic graphical models can structure complex interaction data and support future investigations into multimodal processes in early socialcognition. SUMMARY: A Bayesian-network framework is proposed to model multivariate sequential dependencies in naturalistic mother-child interaction. The order of sequential interaction (OSI) quantifies interaction complexity from behavioral time-series data. Higher OSI is associated with greater prosocial behavior and with neural (rTPJ, lIFG) and physiological (facial EMG) responses during social processing. Interaction complexity is not associated with general cognitive or language measures, suggesting that it reflects a distinct dimension of social behavior. The proposed framework provides a basis for studying social-cognitive development from naturalistic interaction data.

This article scientifically and theoretically analyzes the pedagogical conditions and factors of forming nonverbal communicative skills in future teachers. The concept of nonverbal communication, its components and role in the pedagogical process are considered. The study identifies external and internal factors that influence the development of nonverbal skills in the professional training of future teachers. The components of the pedagogical personality such as nonverbal behavior: gestures, facial expressions, eye contact, spatial and temporal relationships are analyzed. The effectiveness of practical exercises, role-playing games, video analysis and reflexive techniques in the formation of nonverbal communicative abilities is proven.

To explore workplace violence (WPV) amongst Latvian undergraduate nursing students during clinical placements. Workplace violence has profound consequences. Nursing students on placement are often victims of non-verbal and verbal abuse, physical or sexual violence, causing psychological problems, hindering their professional identity and causing them to leave the nursing profession. Numerous studies indicate the problem's extent, yet reporting in the Baltic region has been absent in the literature. Cross-sectional survey. This study, conducted October to December 2023, was based on similar studies in Australia and the UK, using a validated 4-point Likert scale with 24 questions assessing WPV. Questions were uploaded to a commercial internet survey provider, distributed across three universities providing nursing programs in Latvia. Ethical approval was obtained from the University of Latvia's Ethics Committee. Participation was voluntary, involving 119 students (21% from three universities). STROBE checklist: cross-sectional studies. The majority of nursing students (52.9%) on placement experienced bullying (n = 63). Perpetrators included registered nurses and patients. Exposure included negative non-verbal behaviour (69.8%, n = 83), being ignored (55.5%, n = 66), neglected (52.1%, n = 62), and unfairly criticized (51.3%, n = 61). Only 13.4% (n = 16) reported these episodes. There was a significant association between bullying and students considering leaving the nursing profession. Latvian nursing students experience various forms of WPV, including emotional bullying (e.g., negative non-verbal behaviour, being ignored, neglected, unfairly criticized, verbally abused), physical abuse (e.g., being pushed), sexual harassment (e.g., inappropriate touching, sexist remarks). The lack of reporting may result in unresolved issues for both students and nursing profession. Clinical nurses working directly in healthcare settings and academic facilitators/lecturers involved in teaching and training should collaborate on implementing targeted training programs addressing WPV. This ensures that both practical and theoretical WPV-handling aspects are covered comprehensively. None.

A scoping review of patient-provider communication about weight and weight management among adults with higher body weight.

Shared book reading (SBR) is a pivotal activity in early childhood language development. However, children using cochlear implants (CIs) face challenges due to their auditory difficulties and the need for adapted communication strategies. This study aims to compare the maternal interactions during SBR by mothers of children with CIs and typically developing (TD) children. Fifteen mothers of children with CIs and 20 mothers of TD children participated in the study. Each of them was given a picture-salient and a print-salient book to read to their child in any order. The interactions were video recorded and analyzed. Mothers of children with CIs exhibited significantly more verbal and nonverbal behaviors compared to mothers of TD counterparts, particularly nonverbal references, which displayed a large effect size. Notably, while mothers of children with CIs showed significant differences in nonverbal references across both book types, mothers of TD children showed marked differences in verbal behaviors, including non-immediate talk, written text, and engagement with books. Additionally, analysis revealed that the correlation between the language proficiency of the mother and various verbal behaviors in both groups highlighted its importance in language development. Furthermore, the duration of therapy was significantly linked to the use of nonverbal references and providing text by mothers of children with CIs. The study sheds light on the variations in maternal interaction in accordance with the types of books and also highlights the use of decontextualized language during SBR.

More than ears: Neural synchrony underlies the facilitating effects of active listening on reappraisal over acceptance during interpersonal emotion regulation.

A core challenge of inclusive education lies in the difficulty teachers face in effectively identifying and responding to the diverse behavioral manifestations of students with special educational needs (SEN) in mainstream classrooms. Traditional observation methods are time-consuming, labor-intensive, and highly subjective. This paper explores the application potential of computer vision (CV) technology in this field, aiming to construct an objective and automated framework for classroom behavior analysis. We propose a multimodal fusion method based on pose estimation and spatiotemporal modeling, capturing students' nonverbal behaviors in the classroom (such as body posture, head orientation, and activity level) using an RGB camera and combining this with simple audio features (vocal activity) for comprehensive analysis. We collected a dataset containing behavioral patterns of typical SEN students (such as Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD)) in a simulated inclusive education classroom environment and validated the proposed method. Experimental results show that the system achieves high accuracy (average 85.2%) in identifying key behavioral indicators (such as "attention," "social interaction," and "Atypical sports pattern"), significantly outperforming baseline methods that rely solely on manual observation. This study demonstrates the effectiveness of computer vision technology as a professional support tool for teachers, providing a new technological approach for achieving precise and personalized inclusive educational interventions.

The Praecox Feeling refers to clinicians' immediate sense of disturbed interpersonal contact when encountering individuals with schizophrenia. Although considered subjective, this experience persists in clinical practice through the PANSS Poor rapport item, used as an indirect operational proxy. The behavioral substrates underlying this judgment remain insufficiently specified. We examined whether objectively quantified gestural behavior during first contact relates to clinician-rated Poor rapport and whether interaction partners adapt their nonverbal behavior accordingly. Naïve interaction partners (IP) engaged in two first-contact interactions, one with an individual with schizophrenia (ISZ) and one with a matched control (MAT), in an ecological setting. Gestural expansiveness was quantified using automatic motion tracking. Poor rapport was assessed independently during a subsequent standardized PANSS interview conducted by a trained psychiatrist not involved in the interaction. Within the schizophrenia group, reduced gestural expansiveness during first contact was associated with higher clinician-rated Poor rapport. No significant group difference in gestural expansiveness was observed between ISZ and MAT. However, interaction partners showed reduced gestural expansiveness when interacting with ISZ. Ecologically measured gesture kinematics were associated with independently assessed clinician-rated interpersonal disturbance. These findings suggest that Praecox Feeling may reflect clinicians' sensitivity to subtle, measurable alterations in embodied interpersonal dynamics that generalize across interactional settings. Disturbed social contact appears to emerge within a dyadic system rather than from individual behavior alone. Objective movement markers may contribute to operationalizing early interpersonal disturbance and may contribute to refining the phenomenological construct of Praecox Feeling.

Patient experience is shaped not only by the technical success of surgical care but also by the emotional and relational signals conveyed by the surgeon. Surgeon emotional signaling—defined as verbal, non-verbal, and cognitive expectation-setting behaviors—represents a modifiable clinical competency influencing the patient experience. Contemporary literature from surgical communication science, behavioral medicine, and clinician well-being research supports the integration of confidence-aligned communication into routine surgical practice. Using heuristic archetypes derived from clinical experience and supported by literature synthesis, this commentary illustrates how surgeon demeanor may influence psychological and behavioral recovery trajectories. Practical tools and system-level recommendations are provided to support implementation.

This paper examines the leadership approach of a Shingo exemplar leader, focusing on principles and practices that address contemporary organizational challenges and the evolving expectations of Generation Z. Using a qualitative multi-method design, the study integrates interviews, surveys, participant observation, and narrative analysis to explore both verbal and nonverbal leadership behaviors. Triangulation strengthens reliability, while non-parametric analysis and descriptive statistics support interpretation. Findings suggest that traditional, tool-focused Lean models are insufficient for long-term organizational sustainability, as they often overlook the human and psychological foundations of performance. The study emphasizes the importance of language, nonverbal communication, and micro-behaviors in shaping leadership effectiveness. It further demonstrates how integrating psychological constructs – such as proactive personality, growth mindset, outward mindset, intrinsic motivation, learned optimism, and meaning – enables a more holistic, human-centered approach to operational excellence. This perspective aligns closely with the Shingo Model and resonates strongly with Generation Z’s emphasis on purpose, development, and meaningful work. The originality of the research lies in its interdisciplinary integration of storytelling with insights from psychology, neuroscience, and sociology, contributing to a mid-range theory that explains how leadership behaviors and psychological factors enhance the sustainable impact of Lean in engaging the emerging workforce.

BackgroundHealth care workers (HCWs) face sustained psychological demands that place them at heightened risk for burnout and posttraumatic stress disorder (PTSD). However, assessing psychological distress in this population remains challenging because of stigma, underreporting, and the limitations of self-report tools. Although nonverbal behaviors such as facial expressions and gaze hold diagnostic promise, most approaches overlook the fine-grained, temporal fluctuations in these signals. In this study, we focused on microbehavior intervals—brief, involuntary changes in multimodal nonverbal signals—that emerge during emotion-eliciting interviews.ObjectiveThis study aimed to determine whether microbehavior intervals improve the discrimination of psychological distress profiles among HCWs with symptoms of burnout and PTSD.MethodsHCWs participated in a semistructured interview that included 5 work-related, emotionally charged questions and that was recorded via Webex (online video platform). Participants also completed validated questionnaires for burnout (Maslach Burnout Inventory General Survey 9-item) and PTSD (PTSD checklist for Diagnostic and Statistical Manual, 5th edition). Recordings were analyzed with computer vision models to generate time-series data of facial expressions, head movement, gaze, body posture, and hand gestures. An unsupervised anomaly detection model (MOMENT [a Family of Open Time-Series Foundation Models]) isolated microbehavior intervals without requiring manual labels. Features derived from these intervals were used to train a deep learning classifier that predicted 4 symptom classes of psychological distress: “moderate-severe burnout,” “subthreshold-provisional PTSD,” “burnout+PTSD,” and “resilient.” We conducted an ablation study by systematically removing one behavioral data stream at a time. Finally, we conducted an explainability analysis to characterize the features driving model predictions.ResultsWe analyzed 258 interview recordings from 151 HCWs. Per interview, an average of 19.65 (SD 6.01) microbehavior intervals were detected, each lasting an average of 1.31 (SD 1.10) seconds. The classifier demonstrated robust performance across classes, achieving a macro– F1-score of 0.75 and a macro area under the receiver operating characteristic curve of 0.80 on held-out data. Ablation analysis showed that excluding gaze or arousal-valence signals caused the largest performance declines, particularly in recall and F1-score. The explainability analysis revealed distinct temporal patterns across symptom classes, with irregularity and variability in microbehaviors emerging as key predictors.ConclusionsFocusing on microbehavior intervals yields a scalable, interpretable, and annotation-free framework for detecting psychological distress from nonverbal signals. By moving from whole-video features to fine-grained multimodal temporal modeling, we successfully captured subtle, involuntary fluctuations in nonverbal responses to emotion-eliciting questions. This multimodal approach enables an objective, robust, and explainable assessment of psychological distress and offers a promising complement to conventional psychometric assessments.

ABSTRACT The visible non-verbal behaviour of table tennis dyads after a rally can convey meaningful information about the players’ internal state. Because these behavioural cues often reflect affective processes, understanding the situational factors that shape their intensity can deepen insight into how affect emerges and fluctuates during performance and inform regulation strategies. Building on this idea, in the present study, we aimed to assess whether the point outcome (i.e., win/loss) or the importance of the situation (i.e., beginning/end of a set) would influence how well this kind of non-verbal behaviour can be recognised. To this end, 104 participants were shown 40 video excerpts with the non-verbal behaviour of male table tennis dyads of the German first division immediately after a rally. After each video excerpt, they were asked to estimate whether the table tennis dyads shown just won or lost a point. The overall recognition rate was 86.93%. The results further showed that the recognition rates did not significantly differ between won (87.79%) and lost (85.87%) rallies, however, they were significantly higher for situations at the end (89.52%) than at the beginning (84.14%) of a set. Considering the interaction between point outcome and the importance of the situation, the results further showed that recognition rates for lost rallies at the end of a set (91.44%) were higher than for lost rallies at the beginning of a set (80.29%), while the recognition rates between won rallies from the beginning (87.98%) and the end (87.60%) of a set did not significantly differ.

ABSTRACT Video-based analysis of classroom interactions offers valuable insights into user behaviour and engagement, yet manual coding remains labour-intensive and difficult to scale. Traditional computer vision models automate some tasks but rely on rigid taxonomies and extensive labelled data, limiting their usability for educators and researchers. This study explores the use of pre-trained video-based Multimodal Large Language Models (MLLMs) to support automated detection of nonverbal behaviours in classroom settings. We compare two models – LLaVA-7B and LLaVA-72B – in identifying key indicators of embodied and collaborative learning (gestures, eye contact, and joint attention). Using video from a simulation-based science activity, we evaluate each model’s accuracy and efficiency. Our results revealed a critical trade-off: the larger model achieved higher accuracy but required significant computational resources, while the smaller, faster model struggled to detect nuanced social cues. Error analysis reveals common misclassifications, underscoring the importance of careful prompt design and behaviour framing. Given these challenges, we conclude that MLLMs are currently best used as assistants within a human-in-the-loop workflow, where they function as a ‘first-pass’ filter while the human users retain final interpretation. This work provides empirical evidence and practical guidance for integrating generative AI into behaviour analysis workflows.

IntroductionDevelopmental Language Disorder (DLD) is a common neurodevelopmental condition that affects both the structural and pragmatic aspects of language. Conversational abilities—including topic initiation, maintenance, repair, turn-taking, and the integration of non-verbal behaviors—are essential for social communication and peer relationships. While a substantial body of research has described conversational difficulties in DLD among English-speaking populations, there is limited evidence on how these impairments manifest in Mandarin-speaking children. There is a critical need for culturally adapted assessment approaches; thus, this protocol primarily aims to evaluate the feasibility of a multimodal framework tailored specifically to the Mandarin-speaking context.MethodsThis protocol describes an age-stratified cross-sectional observational study with two phases. In Phase 1, an adapted multimodal profiling framework will be developed and piloted through semi-structured free conversation and role-play tasks, recorded with audio–video equipment. Transcription will follow Codes for the Human Analysis of Transcripts (CHAT) conventions within European Distributed Corpora (EUDICO) Linguistic Annotator (ELAN), with word segmentation supported by Jieba and manual correction. Annotation tiers will capture utterance-level features, communicative acts (Inventory of Communicative Acts-Abridged [INCA-A]), repairs, turn-taking, and gesture–speech alignment (stroke apex ±500 ms). Feasibility (session completion, recording length, and utterance yield) and reliability (Cohen’s κ, ICC, and drift checks) will be evaluated to refine the coding manual. In Phase 2, the finalized protocol will be applied to 90 children with DLD and 90 typically developing (TD) peers (aged 4–6, matched for age and sex). Data analysis will quantify primary outcome measures (topic maintenance ratio, successful repair rate, gesture–speech synchrony index) and secondary outcome measures (lexical diversity, initiation–maintenance balance, and turn-taking productivity), with exploratory analyses of demographic and home-environment moderators.DiscussionThis protocol advances methodological research by providing a transparent and reproducible framework for multimodal profiling of pragmatic language in Mandarin-speaking preschoolers. Its strengths include multimodal data integration and explicit feasibility benchmarks. Limitations include the cross-sectional design and a modest sample size. Future research may extend the protocol to longitudinal studies, contributing to the establishment of standardized procedural benchmarks and improved data comparability within this specific linguistic environment.

The goal of this review was to identify and summarize technology-assisted methods that assess nonverbal behaviors known to influence the quality of the therapeutic alliance between health care providers and patients in clinical, research, or educational settings. Strong therapeutic alliances in health care provider-patient relationships contribute to positive patient outcomes. Previous studies have shown that nonverbal behaviors from providers, such as tone of voice, facial expression, eye contact, and physical positioning, help build strong therapeutic relationships. Technological advances have created opportunities to automate detection and feedback about nonverbal behaviors in clinical interactions without the intervention of highly trained instructors. Automated detection and feedback will increase opportunities to develop better nonverbal communication, which is expected to improve the quality of the therapeutic alliance. Participants were current or aspiring health care providers who routinely would be expected to have patient encounters in clinical, educational, or research settings. Interactions could include actual patient interactions, model patients, virtual patients, or simulated patients. Included studies involved technology-assisted methods to collect or analyze at least 1 nonverbal behavior. This review included qualitative and quantitative studies and review articles. PubMed, Embase, CINAHL, ERIC, Scopus, and Google Scholar were searched for published and unpublished literature in English between 2010 and 2023. Two reviewers independently completed title and abstract screening, full-text review, and data extraction. Any conflicts that arose were resolved by a third reviewer. Extraction was completed by 2 reviewers. Twenty-five sources were included. The most frequently measured behaviors included gaze frequency or duration on the patient's face (52% of studies) and facial expression (48%), with 24% of studies measuring social touch or speech patterns, 20% measuring posture and gestures, 12% measuring proximity to patient, 8% measuring synchrony, and 4% measuring voice. Technologies for data collection included audio or video recordings and other technologies such as eye-tracking glasses or multi-functional headsets, used alone or integrated into augmented reality or virtual reality systems. Challenges associated with analyzing data included recognition of patients' and providers' voices, facial features, and body parts, and classifying body posture and movement as well as facial expression and movements. Studies used commercial, open source, or customized software to meet each challenge. Many incorporated machine learning or algorithms associated with artificial intelligence (AI), which required significant training data. Technology-assisted methods for analyzing voice and social touch were limited, whereas there were several available analysis techniques for analyzing synchrony, gestures, posture, and proximity to patients. The use of technology in collection and analysis of provider-patient interactions to enhance nonverbal behaviors and communication skills is rapidly developing, with multiple options available. Future efforts should focus on technology-assisted methods to analyze voice and social touch, and should transparently report contributing factors and training data for machine learning models or AI-associated algorithms. Development of systems will require significant testing to ensure accessibility to the intended audience and broadly accurate and meaningful nonverbal behaviors. OSF ( https://osf.io/kedmf ).

Aim. To analyze representation of silence as a key detail in the psychological portrait of the main character in N. S. Leskov’s story “The Life of a Woman.” Methodology. The study used methods of discourse and contextual analysis, the method of studying dictionary definitions, and the descriptive-analytical method. Results. The study concluded that the representation of silence as an essential component of nonverbal behavior in various discursive situations is a key detail in creating the psychological portrait of the protagonist of “The Life of a Woman.” It is silence, both involuntary and symptomatic, and intentional and semiotic, that conveys the most complex nuances of Nastya Prokudina’s mental state and her communicative intentions. Research implications. The results of the article can be used to solve similar research problems.

This article examines nonverbal means of expressing the category of compatibility using the example of communicative interactions between the leaders of Russia and China, covered by media resources from 2013 to 2025. The theoretical framework of the study includes ideas from nonverbal semiotics, social psychology, as well as modern theories of embodied cognition and trust synchronization. Methods of thematic, semantic, and discourse analysis are used. The results of the study demonstrate the evolution of the nonverbal behavior of state leaders from formal and protocol-based (2013–2015) to informal and friendly, in which nonverbal elements play a significant role – communicative distance between subjects, gestures, facial expressions, tactile and visual contact (2013–2025). It has been established that as political relations between Russia and China develop, their leaders increasingly use nonverbal elements in communicative interactions, which is reflected in photo chronicles of meetings of the heads of state.

Effective communication and empathy are core competencies in patient-centred dental care. However, structured training in these skills is often limited in dental curricula. This study explored the association between a structured communication and body language course and dental students awareness of nonverbal communication, empathy-related attitudes, and patient-centred perspectives. A cross-sectional study was conducted among 390 final-year dental students at Ankara University Faculty of Dentistry. Group 1 (n = 195) had not received formal communication training, whereas Group 2 (n = 195) had completed a 39 h structured course including theoretical and practical components. Data were collected using a structured questionnaire covering sociodemographic characteristics, communication awareness, nonverbal communication practices, and empathy-related attitudes. Group differences were analysed using chi-square tests for categorical variables and independent samples t-tests for composite scores, with a p < 0.05 considered statistically significant. Students who received training reported significantly higher awareness of the role of body language (p = 0.035), greater support for its inclusion in the curriculum (p = 0.037), and increased attention to instructors' nonverbal cues (p = 0.0028). They also reported more frequent use of positive nonverbal behaviours, such as maintaining eye contact (97.4% vs. 92.0%, p = 0.042), using gestures and facial expressions (93.8% vs. 84.3%, p = 0.028), and adjusting tone of voice (90.8% vs. 80.1%, p = 0.014). Empathy-related attitudes were significantly stronger in the trained group, including better recognition of patients' emotions (88.3% vs. 76.5%, p = 0.015), greater comfort in showing empathy (85.3% vs. 70.8%, p = 0.007), and a stronger belief that empathy can be taught (88.5% vs. 74.1%, p = 0.008). The overall mean scores for communication awareness, nonverbal communication, and empathy-related attitudes were all significantly higher in the trained group (p < 0.05). Structured communication and body language training significantly enhance dental students awareness and use of nonverbal communication and strengthen empathy-related attitudes. Integrating experiential communication training into dental education may support the development of more empathetic, patient-centred clinical practice.