Search Results (1,062)

Interest in general AI is widespread, and much is expected from its large-scale adoption in the healthcare sector. However, the success of uHealth implementations relies on genuine trust, beyond technical performance. Neuroception of psychological safety (NPS), grounded in polyvagal theory, encompasses the human subconscious and automatic processes of safety and risk detection. We conducted a cross-sectional survey to explore a hypothetical connection between NPS and the perception of general AI in the uHealth context, by an anonymous online questionnaire comprising the following: Neuroception of Psychological Safety Scale (NPSS), four-item AI Attitude Scale (AIAS-4), and questions on AI threat, age, gender, and level of education. Multivariate analysis was performed using covariance-based structural equation modeling. We received 201 responses: 73 (36.3%) males vs. 128 (63.7%) females, all adults with varying levels of education (from 0 = basic formal education to 4 = master’s degree). Respondents belonged to four demographic cohorts: from Baby boomers to Generation Z. SEM results indicated that attitudes towards AI-driven health interventions are significantly impacted by social engagement and compassion (NPSS factors). Gender, education, and demographic cohort were confirmed as significant covariates. NPS-related attitudes towards AI should be considered and analyzed by healthcare providers, application developers, and policy or regulatory authorities. Full article

This study aimed to examine the effects of online, video-based teacher professional development on changes in classroom instruction and student achievement in biology. The professional development program included organizing lessons based on prepared materials aligned with national curriculum outcomes, asynchronous participation in an online forum for (self-)analysis of lesson videos using the Teaching Observation Form (TOF), and synchronous participation in online communities of practice. Teachers and their eighth-grade students participated in this quasi-experimental study, which involved control and experimental student groups and pre- and post-tests of knowledge. The results indicate that students in the experimental group achieved statistically significantly higher post-test scores than those in the control group (d = 0.26), with the largest differences observed in tasks requiring higher-order cognitive skills. The findings suggest that even a relatively short professional development intervention—including continuous online support for teachers—can lead to improvements in student learning outcomes. Full article

This research proposes a composite machine learning (ML) framework for real-time response to negative online reviews, grounded in the psychological principle of negative reinforcement. By integrating K-means clustering to group reviews by thematic similarity and bidirectional encoder representations from transformer (BERT)-based sentiment analysis to assess emotional tone, and the system identifies high-risk clusters requiring marketing intervention. Customized response strategies are designed based on cluster sentiment intensity, and their effectiveness can be evaluated via sentiment transformation functions. The proposed model provides a practical and adaptive approach to digital marketing, enabling brands to respond rapidly, reduce dissatisfaction, and enhance consumer trust in a data-driven environment. Full article

Background/Objectives: Workplace violence (WV) against healthcare workers (HCWs) is a major hazard all over the world. Prevention requires a reliable risk assessment. The rate of HCWs reporting a violent event varies considerably across multi-year retrospective studies compared to periodic surveys. We conducted a rapid observational study to demonstrate that data collection methods are more important than socio-cultural and healthcare organizational differences in determining the frequency of reported violence. Methods: In June 2025, in a cross-sectional observational comparison, we examined a total of 236 nurses divided into three groups: the first two were recruited online from Brescia (Italy) and Trollhättan (Sweden), while the third group was composed of Latium (Italy) nurses participating in a sleep health promotion program who answered the same questions on WV online. All the workers reported the frequency of violent incidents experienced in the previous 12 months using the Violent Incident Form (VIF), occupational stress using the Effort/Reward Imbalance questionnaire (ERI), and work ability via the Work Ability Score (WAS). Results: In the three samples, WV was correlated positively with stress and inversely with work ability (p < 0.01), while no significant difference was found between Italian and Swedish nurses in relation to the spot surveys. The nurses questioned directly about WV were significantly younger and reported significantly higher rates of physical aggression (28% vs. 5%, p < 0.001) and all forms of violence (73% vs. 20%, p < 0.001) than those questioned indirectly during the census of all the HCWs. In a multivariate linear regression model, the WV experienced and poor work ability were highly significant predictors of work-related stress (p < 0.001). Nurses who had experienced WV in the previous year had an increased odds ratio (OR = 8.94; Confidence Interval 95% = 4.43; 18.01) of reporting a state of distress. Conclusions: Experience has shown that specific questioning about violence—the commonest method used—encourages respondents to report violent events and may induce overreporting. This method also tends to involve younger workers who are more exposed to WV. On the other hand, prospective studies based on official reports may be influenced by underreporting. Monitoring WV during health promotion interventions included in occupational health surveillance could minimize both phenomena. Systematic studies and meta-analyses which rely mainly on “ad hoc” studies may be biased. Full article

COVID-19 lockdown announcements triggered global waves of panic buying, leading to widespread panic buying of essential goods and supply chain disruptions. Although the acute phase of the pandemic has passed, panic buying continues to emerge during natural disasters, extreme weather events, and other crisis-related disruptions, highlighting the ongoing need for evidence-based strategies to address its psychological drivers. Social cognition constructs, including willingness, intentions, attitudes, subjective norms, and risk perceptions, have been identified as modifiable psychological predictors of panic buying. However, few studies have experimentally tested theory-driven interventions aimed at modifying these mechanisms. This study evaluated the effectiveness of a brief, online intervention based on integrated social cognition models in reducing panic-buying-related cognitions during a hypothetical lockdown scenario. A pre-registered randomized controlled trial was conducted with Australian grocery shoppers (N = 140), who were randomly allocated to an intervention or control condition. Participants completed self-report measures assessing their willingness, intentions, attitudes, subjective norms, and risk perceptions at both pre- and post-intervention times. The hypotheses were partially supported. Compared with the control condition, the intervention group reported greater reductions across targeted psychological constructs. For hygiene products, significant decreases were observed across all five constructs, and for non-perishable foods, willingness, intention, and attitudes significantly decreased. For cleaning products, reductions were evident for attitudes, subjective norms, and intentions. These findings suggest that theory-informed, scalable interventions can effectively modify the social cognition processes underlying panic buying. This study extends existing research and demonstrates the potential for brief, theory-based communication strategies to reduce panic-buying-related cognitions. Future research should evaluate these interventions in real-world settings and explore mechanisms to target automatic cognitive processes. Full article

Wearable technologies, such as smartwatches, are increasingly used by people with Chronic Obstructive Pulmonary Disease (COPD) for health monitoring and self-management. However, there is limited evidence-informed guidance available to help patients and healthcare practitioners use these tools effectively in everyday life. Objectives: This study aimed to co-create a digital resource for people with COPD and healthcare practitioners to support the use of smartwatches for self-management. Methods: A participatory co-creation methodology was used, based on the Three Co’s Framework (co-define, co-design, co-refine). Participants included people with COPD, carers, family, or friends of people with COPD; healthcare practitioners; and researchers who attended workshops and individual think-aloud interviews to develop a website and video resource. The resource was refined based on real-time feedback. Data were analysed using rapid qualitative analysis. Results: Twenty-one participants engaged and identified key informational needs, including understanding smartwatch features, interpreting health data, and setting personalised goals. The co-created website and video resource were positively received. Participants valued the inclusion of real-life experiences and practical guidance tailored to both patients and healthcare practitioners. Conclusions: This study presents the first co-created resource for COPD and healthcare practitioners on using smartwatches. The co-creation process was successfully delivered online and face-to-face, demonstrating a robust, inclusive approach to managing multiple stakeholders. The resource offers practical value for patients and practitioners and contributes to the growing field of remote interventions for chronic respiratory conditions. Future research is needed to evaluate its effectiveness. Full article

With the development of the internet and the increasing maturity of social media ecosystems, online collective actions within digital social networks have become more frequent and exhibit new patterns. Research on the mechanisms and governance of online collective action has become a crucial aspect of corporate crisis management. This study constructs an online social network with scale-free (BA) characteristics, defines individual properties and interaction rules based on the SIR model, and simulates the outbreak and intervention of online collective actions. The findings indicate that netizens with similar cognitions spontaneously form virtually clustered groups under the influence of triggering events, progressing through emotional arousal, emotional expression, and emotional mobilization, ultimately leading to large-scale online collective action. Collective actions initiated by opinion leaders tend to be more widespread, sudden, and persistent. To mitigate online collective actions, companies should enhance the transparency of core event information, promptly address the demands of action groups, soothe public sentiment, respond to societal concerns, and strengthen guidance over opinion leaders in public discourse. Full article

Background: Although there is a considerable body of research evidence on active school travel (AST), the number of children walking to school has decreased over the years in Australia, as well as around the world. Different factors influence AST; the most cited in Melbourne is traffic safety perception. Traffic safety perception is influenced by built environment elements, and improving the built environment can enhance parental perception of traffic safety. Studies have shown that lateral separation from traffic and the provision of a buffer improve the perception of traffic safety, and this has to be explored for children walking to school based on the existing ground situation on a typical street near a school in Melbourne. Based on this background, a pilot study was carried out before the main study to test the reliability and validity of the survey questionnaire. Methods: The survey instrument was developed based on perceptions and/or AST studies, and included safety and probability aspects of the perception construct to elicit responses on perception. The perception of traffic safety was to be rated based on the streetscape videos embedded in the survey. The reliability was tested using Cronbach’s alpha and validity was explored through exploratory factor analysis. The study also checked the feasibility of the recruitment method and whether there would be an observable outcome from the study. The participants were recruited online through community Facebook groups. Results: The survey instrument had excellent reliability (α = 0.945) and was valid. The recruitment method through a Facebook community group was apt for recruiting participants. The preliminary analysis of the pilot data revealed a difference in perception ratings based on the streetscape element intervention. Conclusions: The survey instrument can be used for similar AST research, as it proved to be reliable and valid. Full article

This paper proposes a fast epileptic seizure detection method to allow for early clinical intervention. The primary goal is to enhance computational and predictive performance to make the method viable for online implementation. An advanced Line Spectral Estimation (LSE)-based method for EEG analysis was developed with Bayesian inference and Toeplitz structure-based fast inversion with Capon and non-uniform Fourier transforms to reduce computational requirements. XGBoost classifier with parallel boosting was employed to increase prediction performance. The method was tested with patients’ EEG data using multiple embedded Graphic Processing Unit (GPU) platforms and achieved 95.5% accuracy, and 23.48 and 33.46 min average and maximum lead times before a seizure, respectively. The sensitivity and specificity values (92.23% and 93.38%) show the method to be reliable. The integration of LSE and XGBoost can be extended to create an efficient and practical online seizure detection and management tool. Full article

Stroke survivors often experience psychological difficulties, yet specialist provision is limited. The Wellbeing After Stroke (WAterS) study co-developed a nine-week, online Acceptance and Commitment Therapy (ACT) group programme designed to be delivered by non-specialist practitioners using structured, script-informed session clinical protocols. This study explored whether fidelity of delivery could be assessed, both to the clinical protocol (what was delivered) and to ACT therapeutic processes (how it was delivered). Eight practitioners were trained, and four delivered the intervention to three groups of four stroke survivors. Fidelity was assessed using a bespoke WAterS checklist, completed by practitioners after each session, and the ACT-Fidelity Measure (ACT-FM), completed by researchers rating a sub-set of recorded sessions. Practitioners delivered 92–100% of planned content, indicating high fidelity to protocol. ACT-FM ratings suggested some consistency with ACT processes, though there was variability across practitioners. These findings provide preliminary, proof-of-principle evidence that non-specialists can deliver a structured ACT-based group intervention with fidelity to protocol, and that both self-completed and observer-rated methods can feasibly assess fidelity. However, the small sample size means these results should be considered exploratory. The study highlights the potential value of these methods for informing training and fidelity assessment in future research. Full article

Critical thinking, regarded as an indispensable high-order thinking for pre-service teachers, is of great significance in effective teaching and the cultivation of students’ critical thinking. Given that it has been confirmed by previous studies that the development of pre-service teachers’ critical thinking can be promoted by microteaching, a “Practice-Feedback-Journal” microteaching model was innovatively constructed in this study, aiming to cultivate the critical thinking of pre-service teachers. To investigate the impact of this model, 41 participants from a Chinese normal university were selected for a 12-week microteaching intervention experiment. Subsequently, content analysis of their online reflective journals was conducted using the Nvivo 20 software, based on the critical thinking framework. The findings suggest that the model has the potential to enhance Chinese pre-service teachers’ critical thinking. Evidence indicates that reflective feedback and case-based teaching strategies appear supportive, while cooperative learning also emerged as a promising approach due to its dual simulation of both student and teacher perspectives. As a small-scale exploratory study, this research offers preliminary insights and potential avenues for cultivating higher-order thinking in teacher education. Full article

Objective: This study aimed to identify caregivers’ perceptions, preferences, and intentions regarding the use of digital articulation therapy applications for children with DLD. Methods: A cross-sectional online survey was conducted between August and September 2025 among 197 caregivers of children diagnosed with DLD. A 43-item questionnaire was structured into five domains addressing demographics, therapy experience, digital-therapy exposure, and preferences for application-based articulation therapy. Constructs from the Unified Theory of Acceptance and Use of Technology 2, including performance expectancy (PE), social influence (SI), price value (PV), facilitating conditions (FC), and behavioral intention, were analyzed. Results: Most respondents were mothers (96%), and 78.7% of them resided in urban areas. Among them, 84.3% had prior speech therapy experience. Only 15.7% had used educational or therapeutic applications; the main dissatisfaction factors were lack of fun (51.6%) and feedback (19.3%). Caregivers preferred short, engaging sessions (20–40 min per day), video-based (75%) or game-based (64%) content, and feedback every 2 months, with a reasonable monthly cost (20,000–30,000 KRW). Regression analysis revealed that sex (β = −0.451, p = 0.013), PE (β = 0.381, p < 0.001), and PV (β = 0.212, p = 0.034) significantly associated with behavioral intention to use an articulation-therapy application, whereas SI and FC were not significant. Conclusions: Caregivers of children with DLD demonstrated strong willingness to adopt digital articulation therapy applications, particularly when these tools provide meaningful therapeutic outcomes at moderate cost and include motivating, interactive content. Future application design should prioritize treatment functionality, user engagement, and accessibility to enhance adoption and continuity of digital speech-language interventions. Full article

Insects constitute a vital component of terrestrial ecosystems, yet their ongoing global decline underscores the urgency of identifying the factors that facilitate or hinder public engagement in their conservation. This study identifies the key psychological drivers of insect-related conservation behavior within a Romanian context, an understudied geographical and sociocultural setting. Using data collected from 346 adult respondents via an online questionnaire, the predictive performance of the Value–Belief–Norm (VBN) theory, the Theory of Planned Behavior (TPB), and an integrated VBN–TPB framework was examined through Partial Least Squares Structural Equation Modeling (PLS-SEM). The VBN model exhibited superior explanatory power relative to TPB, with biospheric values, ecological worldviews, and personal moral norms emerging as the most influential determinants of behavioral intention and self-reported action. Although participants demonstrated moderate levels of general entomological knowledge, awareness of specific insect-friendly practices was notably limited and frequently characterized by misconceptions. Perceived barriers, particularly informational deficits, time constraints, and financial considerations, exerted significant inhibitory effects on conservation engagement. The findings indicate that effective interventions must extend beyond knowledge transmission, incorporating strategies that activate moral norms, strengthen affective and identity-based motivations, and reduce structural barriers to action. Full article

Sarcopenic obesity, the coexistence of excess adiposity with loss of muscle mass and function, is becoming increasingly prevalent. The condition is linked to higher morbidity and mortality but its diagnosis remains limited by reliance on body composition methods that are costly, inaccessible, and/or involve radiation exposure. Recent advances in bioinformatics, data analytics, and digital health technologies create opportunities for scalable, precise approaches to detection. This narrative review synthesizes current evidence from the published literature on online medical libraries (Pubmed, Medline, Scopus, Google Scholar) until September 2025 on multi-omics, digital phenotyping and eHealth research, highlighting how these tools can refine risk stratification and extend diagnostic reach beyond traditional methods. We describe the potential utility of wearable sensor technologies, and smartphone-based body composition methods, as well as genomics, proteomics, transcriptomics and metabolomics. Such approaches, alone or in combination, may enable earlier identification of sarcopenic obesity, including in individuals who are not routinely prioritized for screening. We conclude that integrating biological and digital data offers promise for advancing precision diagnostics in sarcopenic obesity, enabling more tailored prevention and intervention strategies while ultimately reducing healthcare burden. Further research is required to determine the feasibility, clinical utility and scalability of such innovations before their widespread implementation. Full article

Background/Objectives: Burnout, caused by chronic workplace stress, encompasses emotional exhaustion, depersonalization, and low personal accomplishment. Over half of healthcare professionals experience burnout, leading to increased turnover. Third-wave cognitive behavioral therapies are effective in managing burnout. This study aimed to synthesize existing evidence on third-wave cognitive behavioral therapies and evaluate its effectiveness in reducing burnout among healthcare professionals. Methods: We systematically searched eight databases for studies published through May 2024. The eligible studies included randomized controlled trials and quasi-experimental designs evaluating third-wave cognitive behavioral therapies on burnout in healthcare professionals. A meta-analysis was conducted by applying fixed- and random-effects models. Results: A total of 5005 records were identified, of which 29 were reviewed and summarized, and 11 were included in the meta-analysis. Most interventions utilized mindfulness-based techniques (n = 26) with delivery methods including on-site (n = 16), online (n = 12), and hybrid (n = 1) formats. Third-wave cognitive behavioral therapies significantly reduced emotional exhaustion (standardized mean difference [SMD] = −0.686, confidence interval [CI] = −1.237, −0.136, p = 0.0145, I² = 92.5%) and depersonalization (SMD = −0.529, CI = −0.975, −0.083, p = 0.0202, I² = 89.3%), but the effect on low personal accomplishment was not statistically significant (SMD = 0.311, 95% CI = −0.319 to 0.941, p = 0.3338, I² = 89.4%). Conclusions: Third-wave cognitive behavioral therapies should be implemented to reduce emotional exhaustion and depersonalization; future research should target low personal accomplishment and explore approaches beyond mindfulness. Full article