AI in evaluating ambulation of stroke patients: severity classification with video and functional ambulation category scale.

BACKGROUND: The evaluation of gait function and severity classification of stroke patients are important to determine the rehabilitation goal and the level of exercise. Physicians often qualitatively evaluate patients' walking ability through visual gait analysis using naked eye, video images, or standardized assessment tools. Gait evaluation through observation relies on the doctor's empirical judgment, potentially introducing subjective opinions. Therefore, conducting research to establish a basis for more objective judgment is crucial. OBJECTIVE: To verify a deep learning model that classifies gait image data of stroke patients according to Functional Ambulation Category (FAC) scale. METHODS: Gait vision data from 203 stroke patients and 182 healthy individuals recruited from six medical institutions were collected to train a deep learning model for classifying gait severity in stroke patients. The recorded videos were processed using OpenPose. The dataset was randomly split into 80% for training and 20% for testing. RESULTS: The deep learning model attained a training accuracy of 0.981 and test accuracy of 0.903. Area Under the Curve(AUC) values of 0.93, 0.95, and 0.96 for discriminating among the mild, moderate, and severe stroke groups, respectively. CONCLUSION: This confirms the potential of utilizing human posture estimation based on vision data not only to develop gait parameter models but also to develop models to classify severity according to the FAC criteria used by physicians. To develop an AI-based severity classification model, a large amount and variety of data is necessary and data collected in non-standardized real environments, not in laboratories, can also be used meaningfully.

Scalp Cooling in Preventing Persistent Chemotherapy-Induced Alopecia: A Randomized Controlled Trial.

PURPOSE: Current studies of the efficacy of scalp cooling are limited by short-term duration. Therefore, we conducted a randomized controlled trial to evaluate the efficacy of scalp cooling in reducing persistent chemotherapy-induced alopecia (PCIA) 6 months after chemotherapy. METHODS: We conducted an open-label randomized controlled trial comparing scalp cooling versus control in newly diagnosed patients with breast cancer stages I-III scheduled to receive neoadjuvant or adjuvant chemotherapy with curative intent between December 2020 and August 2021. Patients were randomly assigned (2:1 ratio) to scalp cooling or usual clinical practice. The primary outcome was PCIA 6 months after chemotherapy. Hair thickness and density were measured using Folliscope 5.0. CIA-related distress was assessed using the CIA distress scale (CADS), with a higher score reflecting higher stress. RESULTS: The proportion of patients with PCIA at 6 months was 13.5% (12/89) in the scalp-cooling group and 52.0% (26/50) in the control group. The average difference in the change in hair thickness from baseline between the scalp-cooling and control groups was 9.0 µm in favor of the intervention group. The average difference in the change in hair density between intervention and control at the end of the study was -3.3 hairs/cm2. At 6 months after chemotherapy, the average difference in the change in CADS score between the intervention and control groups was -3.2 points, reflecting reduced CIA-related stress in the intervention group. CONCLUSION: Scalp cooling reduced the incidence of PCIA, primarily by increasing hair thickness compared with control. Scalp cooling is helpful in promoting qualitative hair regrowth. Yet, further research is necessary to observe longer-term benefits of scalp cooling.

Stable Zinc Electrode Reaction Enabled by Combined Cationic and Anionic Electrolyte Additives for Non-Flow Aqueous Zn─Br2 Batteries.

Aqueous zinc-bromine batteries hold immense promise for large-scale energy storage systems due to their inherent safety and high energy density. However, achieving a reliable zinc metal electrode reaction is challenging because zinc metal in the aqueous electrolyte inevitably leads to dendrite growth and related side reactions, resulting in rapid capacity fading. Here, it is reported that combined cationic and anionic additives in the electrolytes using CeCl3 can simultaneously address the multiple chronic issues of the zinc metal electrode. Trivalent Ce3+ forms an electrostatic shielding layer to prevent Zn2+ from concentrating at zinc metal protrusions, while the high electron-donating nature of Cl- mitigates H2O decomposition on the zinc metal surface by reducing the interaction between Zn2+ and H2O. These combined cationic and anionic effects significantly enhance the reversibility of the zinc metal reaction, allowing the non-flow aqueous Zn─Br2 full-cell to reliably cycle with exceptionally high capacity (>400 mAh after 5000 cycles) even in a large-scale battery configuration of 15 × 15 cm2.

Patterns of comorbid PTSD, depression, alcohol use disorder, and insomnia symptoms in firefighters: A latent profile analysis.

BACKGROUND: Firefighters are an at-risk population for multiple psychiatric conditions, including posttraumatic stress disorder (PTSD), depression, alcohol use disorders (AUDs), and insomnia. These disorders are likely to co-occur; however, patterns of comorbidity have scarcely been investigated in firefighters. We aimed to identify subgroups of comorbidity of PTSD, depression, AUDs, and insomnia in a nationwide population of firefighters in South Korea. METHODS: A total of 54,054 firefighters responded to an online survey. Latent classes of comorbidity were categorized using latent profile analysis (LPA) based on the symptom scores of PTSD, depression, AUDs, and insomnia. Analysis of variance was performed to compare the characteristics of the identified classes, and multinomial logistic regression was conducted to examine whether anger reactions, resilience, and number of traumatic events predicted class membership. RESULTS: The LPA identified four subgroups: minimal symptoms (n = 42,948, 79.5 %), predominant PTSD (n = 2858, 5.3 %), subthreshold symptoms and comorbidity (n = 7003, 13.0 %), and high symptoms and comorbidity (n = 1245, 2.3 %). Three comorbidity classes were defined based on severity and one class showed predominant PTSD symptoms. Number of traumatic exposures predicted predominant PTSD, while resilience and anger reactions predicted severity of comorbidities. LIMITATIONS: The cross-sectional design and usage of self-reported questionnaires are limitations of this study. CONCLUSIONS: The severity of PTSD, depression, AUDs and insomnia tend to correlate and co-occur in firefighters. Our findings highlight the need to assess comorbid symptoms in firefighters and need to reduce anger reactions and enhance resilience in those with multiple comorbidities.

In-depth correlation analysis between tear glucose and blood glucose using a wireless smart contact lens.

Tears have emerged as a promising alternative to blood for diagnosing diabetes. Despite increasing attempts to measure tear glucose using smart contact lenses, the controversy surrounding the correlation between tear glucose and blood glucose still limits the clinical usage of tears. Herein, we present an in-depth investigation of the correlation between tear glucose and blood glucose using a wireless and soft smart contact lens for continuous monitoring of tear glucose. This smart contact lens is capable of quantitatively monitoring the tear glucose levels in basal tears excluding the effect of reflex tears which might weaken the relationship with blood glucose. Furthermore, this smart contact lens can provide an unprecedented level of continuous tear glucose data acquisition at sub-minute intervals. These advantages allow the precise estimation of lag time, enabling the establishment of the concept called 'personalized lag time'. This demonstration considers individual differences and is successfully applied to both non-diabetic and diabetic humans, as well as in animal models, resulting in a high correlation.

Novel air-liquid interface culture model to investigate stiffness-dependent behaviors of alveolar epithelial cells.

Pulmonary alveoli are functional units in gas exchange in the lung, and their dysfunctions in lung diseases such as interstitial pneumonia are accompanied by fibrotic changes in structure, elevating the stiffness of extracellular matrix components. The present study aimed to test the hypothesis that such changes in alveoli stiffness induce functional alteration of epithelial cell functions, exacerbating lung diseases. For this, we have developed a novel method of culturing alveolar epithelial cells on polyacrylamide gel with different elastic modulus at an air-liquid interface. It was demonstrated that A549 cells on soft gels, mimicking the modulus of a healthy lung, upregulated mRNA expression and protein synthesis of surfactant protein C (SFTPC). By contrast, the cells on stiff gels, mimicking the modulus of the fibrotic lung, exhibited upregulation of SFTPC gene expression but not at the protein level. Cell morphology, as well as cell nucleus volume, were also different between the two types of gels.

Deep learning model for classifying shoulder pain rehabilitation exercises using IMU sensor.

BACKGROUND: Artificial intelligence is being used for rehabilitation, including monitoring exercise compliance through sensor technology. AI classification of shoulder exercise wearing an IMU sensor has only been reported in normal (i.e. painless) subjects. To prove the feasibility of monitoring exercise compliance, we aimed to classify 11 types of shoulder rehabilitation exercises using an AI (artificial intelligence) algorithm in patients with shoulder pain. We had the patients wear an IMU-based sensor, collected data during exercise, and determined the accuracy of exercise classification. METHODS: Data were collected from 58 patients (27 males, 31 females, age range 37-82 years) diagnosed with shoulder diseases such as adhesive capsulitis and rotator cuff disease. 11 types of shoulder pain rehabilitation exercise programs were developed and repeated each exercise ten times per session while wearing an IMU sensor. The study applied the Rectified Linear Unit (ReLU) and the SoftMax as the activation function for hidden layers, the output layer. RESULTS: The acquired data was used to train a DNN model using the multilayer perceptron algorithm. The trained model was used to classify 11 types of shoulder pain rehabilitation exercises. The training accuracy was 0.975 and the test accuracy was 0.925. CONCLUSION: The study demonstrates that IMU sensor data can effectively classify shoulder pain rehabilitation exercises, providing more appropriate feedback for patients. The model can be utilized to establish a system for remotely monitoring patients' exercise performance. The use of deep learning in patient monitoring and rehabilitation has significant potential to bring innovative changes to healthcare service delivery.

Effects of governmental support on clinical nurse educators in South Korea: A repeated cross-sectional study.

AIM: To assess the effectiveness of the Clinical Nurse Educator Support Project and offer valuable insights for supporting nursing education. BACKGROUND: Allocating clinical nursing educators is crucial for supporting novice nurses' transition into the clinical setting and improving their performance. INTRODUCTION: In 2019, the Ministry of Health and Welfare in South Korea implemented the Clinical Nurse Educator Support Project, which involves governmental financial support for the employment of clinical nurse educators. METHODS: This study employed a repeated cross-sectional design to assess the project outcomes. Following the framework of the Kirkpatrick Evaluation Model, secondary data from annual self-program evaluation reports were analyzed to assess program satisfaction, clinical adaptation, and turnover rates of novice nurses. The "Strengthening the Reporting of Observational Studies in Epidemiology checklist" guided the reporting of the study. RESULTS: The project played a pivotal role in enhancing the quality of nursing education. Novice nurses' program satisfaction and clinical adaptation consistently remained high or exhibited an increase. The project led to a decrease in turnover rate among novice nurses, while the coronavirus 2019 pandemic resulted in increased turnover rates due to limited clinical practice opportunities for nursing students. CONCLUSION: Government support for clinical nurse educators has positively impacted the institutionalization of nursing education. The pressing need is to prioritize not only the enhancement of nursing education quality and the improvement of nurses' working conditions but also the development of healthcare policies and programs to effectively respond to unforeseen challenges and crises. IMPLICATIONS FOR NURSING POLICY: Government and healthcare institutions must collaborate to strengthen clinical education, crucial for novice nurses' clinical adaptation. Prioritizing the improvement of nursing education quality and nurses' working conditions is essential. Continuous research and evaluation of the Clinical Nurse Educator Support Project is imperative to assess its impact and make necessary adjustments.

Allergic rhinitis phenotypes with distinct transcriptome profiles in children: A birth cohort.

BACKGROUND: Allergic rhinitis (AR) phenotypes in childhood are unclear. OBJECTIVES: This study sought to determine AR phenotypes and investigate their natural course and clinical and transcriptomic characteristics. METHODS: Latent class trajectory analysis was used for phenotyping AR in 1050 children from birth through 12 years using a birth cohort study. Blood transcriptome analyses were performed to define the underlying mechanisms of each phenotype. RESULTS: Five AR phenotypes were identified: early onset (n = 88, 8.4%), intermediate transient (n = 110, 10.5%), late onset (n = 209, 19.9%), very late onset (n=187, 17.8%), and never/infrequent (n = 456, 43.4%). Children with early-onset AR were associated with higher AR severity and sensitizations to foods at age 1 year and inhalants at age 3 years and asthma symptoms, but not with bronchial hyperresponsiveness (BHR). Children with late-onset AR phenotype associated with sensitizations to various foods at age 1 year but not from age 3 years, and to inhalants from age 7 years and with asthma with BHR. Children with very late-onset AR phenotype associated with sensitizations to foods throughout preschool age and to inhalants at ages 7 and 9 years and with asthma with BHR. Transcriptome analysis showed that early-onset AR was associated with viral/bacterial infection-related defense response, whereas late-onset AR was associated with T cell-related immune response. CONCLUSIONS: Early-onset AR phenotype was associated with sensitization to foods and inhalants at an early age and asthma symptoms, but not with BHR, whereas very late- and late-onset AR phenotypes were positively associated with sensitization to inhalants and asthma with BHR. Transcriptomic analyses indicated that early- and late-onset AR phenotypes had distinct underlying mechanisms related to AR as well.

Contributions of collagen and elastin to elastic behaviours of tendon fascicle.

Tendon exhibits the capacity to be stretched and to return to its original length without suffering structural damage in vivo, a capacity known as elastic recoil. Collagen fibres are aligned longitudinally and elastin fibres mostly run parallel to collagen fibres in tendon. However, their interactions and contributions to tendon elastic behaviours are not well understood. The present study examined functional roles of collagen and elastin in tendon elastic behaviours using a variety of mechanical tests. We prepared three types of fascicle specimens from mouse tail tendon: fascicles freshly isolated, those digested with elastase in PBS to selectively remove elastin, and those incubated in PBS without elastase. A quasi-static tensile test demonstrated that elastase-treated fascicles had higher tangent moduli and strength compared to fresh and PBS fascicles. Cyclic stretching tests showed that fresh and PBS fascicles could withstand cyclic strain at both small and large amplitudes, but elastase-treated fascicles could only behave elastically to a limited degree. Fibre-sliding analysis revealed that fresh fascicles could be elongated both through stretching of collagen fibers and through movement of the fibres. However, elastase-treated fascicles could be stretched only via fibre stretching. This evidence suggests that normal tendons can be extended through both fibre stretching and fibre sliding, whereas tendons without elastin can only extend as much as collagen fibers can withstand. Accordingly, collagen fibres mainly contribute to tendon elastic behaviours by furnishing rigidity and elasticity, whereas elastin provides tendon viscoelasticity and also enables sliding of collagen fibres during elastic behaviours. STATEMENT OF SIGNIFICANCE: The present study revealed distinct mechanical functions of collagen and elastin fibres in elastic behaviours of mouse tail tendon fascicle using a variety of mechanical tests at both microscopic and macroscopic levels. It was demonstrated that collagen mainly governs tendon fascicle rigidity and elasticity, but only possesses limited extensibility, whereas elastin contributes to viscoelasticity and collagen fibre sliding, enabling elastic recoil behaviour against relatively large deformation. By their interactions, tendon can be elongated without suffering major structural damage and withstand a large magnitude of tensile force in response to mechanical loading. Such information should be particularly useful in designing collagen-based biomaterials such as artificial tendons, in that previous studies have merely considered collagen without incorporation of elastin.

Cascade Catalytic Nanoparticles Selectively Alkalize Cancerous Lysosomes to Suppress Cancer Progression and Metastasis.

Lysosomes are critical in modulating the progression and metastasis for various cancers. There is currently an unmet need for lysosomal alkalizers that can selectively and safely alter the pH and inhibit the function of cancer lysosomes. Here an effective, selective, and safe lysosomal alkalizer is reported that can inhibit autophagy and suppress tumors in mice. The lysosomal alkalizer consists of an iron oxide core that generates hydroxyl radicals (•OH) in the presence of excessive H+ and hydrogen peroxide inside cancer lysosomes and cerium oxide satellites that capture and convert •OH into hydroxide ions. Alkalized lysosomes, which display impaired enzyme activity and autophagy, lead to cancer cell apoptosis. It is shown that the alkalizer effectively inhibits both local and systemic tumor growth and metastasis in mice. This work demonstrates that the intrinsic properties of nanoparticles can be harnessed to build effective lysosomal alkalizers that are both selective and safe.

Biomechanical analysis of tendon regeneration capacity of Iberian ribbed newts following transection injury: Comparison to a mouse model.

Adult mammals are known for their poor ability to regenerate tissues, including tendons. On the other hand, urodeles have become an important model in regenerative studies for their remarkable ability to regenerate various body parts and organs throughout life, such as limbs, retinas, or even the brain. However, little is known about their capacity to regenerate injured tendons. If newts can also repair tendons without scar formation, they may be a suitable animal model for tendon regeneration studies in other adult vertebrates. Therefore, the present study used Iberian ribbed newts to characterize mechanical and structural regeneration of tendons following transection, using tensile tests and multiphoton microscopy. A digital flexor tendon in a hindlimb was transected either partially or completely, and regenerated tendon was examined 6 and 12 weeks after the operation. Tensile strength of regenerated tendons was significantly less than normal at 6 weeks, but was remarkably recovered at 12 weeks, reaching levels comparable to those of uninjured tendons. On the other hand, mouse tendons demonstrated poor recovery of strength even after 12 weeks. Multiphoton microscopy revealed that tendon-like collagenous tissue bridges residual tendon stubs in newts, but disorganized scar-like tissue filled the injured location in mice. These findings highlight the remarkable capacity of newts to recover from tendon injury and confirm the utility of newts as a model to study tendon regeneration.

Inertial measurement unit sensor-based gait analysis in adults and older adults: A cross-sectional study.

BACKGROUND: Gait assessment has been used in a wide range of clinical applications, and gait velocity is also a leading predictor of disease and physical functional aspects in older adults. RESEARCH QUESTION: The study aim to examine the changes in IMU-based gait parameters according to age in healthy adults aged 50 and older, to analyze differences between aging patients. METHODS: A total of 296 healthy adults (65.32 ± 6.74 yrs; 83.10 % female) were recruited. Gait assessment was performed using an IMU sensor-based gait analysis system, and 3D motion information of hip and knee joints was obtained using magnetic sensors. The basic characteristics of the study sample were stratified by age category, and the baseline characteristics between the groups were compared using analysis of variance (ANOVA). Pearson's correlation analysis was used to analyze the relationship between age as the dependent variable and several measures of gait parameters and joint angles as independent variables. RESULTS: The results of this study found that there were significant differences in gait velocity and both terminal double support in the three groups according to age, and statistically significant differences in the three groups in hip joint angle and knee joints angle. In addition, it was found that the gait velocity and knee/hip joint angle changed with age, and the gait velocity and knee/hip joint angle were also different in the elderly and adult groups. CONCLUSIONS: We found changes in gait parameters and joint angles according to age in healthy adults and older adults and confirmed the difference in gait velocity and joint angles between adults and older adults.

Identifying facilitators of and barriers to the adoption of dynamic consent in digital health ecosystems: a scoping review.

BACKGROUND: Conventional consent practices face ethical challenges in continuously evolving digital health environments due to their static, one-time nature. Dynamic consent offers a promising solution, providing adaptability and flexibility to address these ethical concerns. However, due to the immaturity of the concept and accompanying technology, dynamic consent has not yet been widely used in practice. This study aims to identify the facilitators of and barriers to adopting dynamic consent in real-world scenarios. METHODS: This scoping review, conducted in December 2022, adhered to the PRISMA Extension for Scoping Reviews guidelines, focusing on dynamic consent within the health domain. A comprehensive search across Web of Science, PubMed, and Scopus yielded 22 selected articles based on predefined inclusion and exclusion criteria. RESULTS: The facilitators for the adoption of dynamic consent in digital health ecosystems were the provision of multiple consent modalities, personalized alternatives, continuous communication, and the dissemination of up-to-date information. Nevertheless, several barriers, such as consent fatigue, the digital divide, complexities in system implementation, and privacy and security concerns, needed to be addressed. This study also investigated current technological advancements and suggested considerations for further research aimed at resolving the remaining challenges surrounding dynamic consent. CONCLUSIONS: Dynamic consent emerges as an ethically advantageous method for digital health ecosystems, driven by its adaptability and support for continuous, two-way communication between data subjects and consumers. Ethical implementation in real-world settings requires the development of a robust technical framework capable of accommodating the diverse needs of stakeholders, thereby ensuring ethical integrity and data privacy in the evolving digital health landscape.

Low-Dose Ionizing Radiation-Crosslinking Immunoprecipitation (LDIR-CLIP) Identified Irradiation-Sensitive RNAs for RNA-Binding Protein HuR-Mediated Decay.

Although ionizing radiation (IR) is widely used for therapeutic and research purposes, studies on low-dose ionizing radiation (LDIR) are limited compared with those on other IR approaches, such as high-dose gamma irradiation and ultraviolet irradiation. High-dose IR affects DNA damage response and nucleotide-protein crosslinking, among other processes; however, the molecular consequences of LDIR have been poorly investigated. Here, we developed a method to profile RNA species crosslinked to an RNA-binding protein, namely, human antigen R (HuR), using LDIR and high-throughput RNA sequencing. The RNA fragments isolated via LDIR-crosslinking and immunoprecipitation sequencing were crosslinked to HuR and protected from RNase-mediated digestion. Upon crosslinking HuR to target mRNAs such as PAX6, ZFP91, NR2F6, and CAND2, the transcripts degraded rapidly in human cell lines. Additionally, PAX6 and NR2F6 downregulation mediated the beneficial effects of LDIR on cell viability. Thus, our approach provides a method for investigating post-transcriptional gene regulation using LDIR.

Dielectric light-trapping nanostructure for enhanced light absorption in organic solar cells.

Dielectric scatterers where Mie resonances can be excited in both electric and magnetic modes have emerged as a promising candidate for efficient light trapping (LT) in thin-film solar cells. We present that light absorption in organic solar cells (OSCs) can be significantly enhanced by a front-sided incorporation of a core-shell nanostructure consisting of a high-refractive-index dielectric nanosphere array conformally coated with a low-refractive-index dielectric layer. Strong forward light scattering of the all-dielectric LT structure enables the absorption in an organic semiconductor to be remarkably boosted over a broad range of wavelengths, which is attributed to interference of a simultaneous excitation of the electric and magnetic dipole resonant modes. The OSC with the LT structure shows the short-circuit current density (Jsc) of 28.23 mA/cm2, which is 10% higher than that of a flat OSC. We also explore how the LT structure affects scattering cross-sections, spectral multipole resonances, and far-field radiation patterns. The approach described in this work could offer the possibility for the improvement of characteristic performances of various applications, such as other thin-film solar cells, photodiodes, light-emitting diodes, and absorbers.

Assessing Stress and Anxiety in Firefighters During the Coronavirus Disease-2019 Pandemic: A Comparative Adaptation of the Stress and Anxiety in the Viral Epidemic-9 Items and Stress and Anxiety in the Viral Epidemics-6 Items Scales.

OBJECTIVE: This study assessed the reliability and validity of the Stress and Anxiety to Viral Epidemics-9 items (SAVE-9) and Stress and Anxiety to Viral Epidemics-6 items (SAVE-6) scales for measuring viral anxiety among firefighters during the coronavirus disease-2019 pandemic. METHODS: An online survey was conducted among 304 firefighters assigned in Gyeonggi-do. The SAVE-9 scale, initially developed for healthcare workers, was adapted for firefighters. We compared it with the SAVE-6 scale designed for the general population among the firefighters sample. The confirmatory factor analysis (CFA) was conducted to explore the factor structure of both scales. Internal consistency reliability was checked using Cronbach's alpha and McDonald's omega. Convergent validity was assessed in accordance with the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7 scales. RESULTS: The SAVE-9 scale demonstrated a Cronbach alpha of 0.880, while the SAVE-6 scale yielded an alpha of 0.874. CFA indicated good model fits for both SAVE-9 and SAVE-6 scales among firefighters sample. The SAVE-9 and SAVE-6 comparably measures viral anxiety of firefighters. CONCLUSION: Both of the SAVE-9 and SAVE-6 scales are reliable and valid instruments for assessing viral anxiety among firefighters during the pandemic.

Discovery of 3-Phenyl Indazole-Based Novel Chemokine-like Receptor 1 Antagonists for the Treatment of Psoriasis.

Chemokine-like receptor 1 (CMKLR1)─a G protein-coupled receptor─has functional roles in the immune system and related diseases, including psoriasis and metabolic diseases. Psoriasis is a chronic inflammatory disease characterized by skin redness, scaliness, and itching. In this study, we sought to develop novel CMKLR1 antagonists by screening our in-house GPCR-targeting compound library. Moreover, we optimized a phenylindazole-based hit compound with antagonistic activities and evaluated its oral pharmacokinetic properties in a murine model. A structure-based design on the human CMKLR1 homology model identified S-26d as an optimized compound that serves as a potent and orally available antagonist with a pIC50 value of 7.44 in hCMKLR1-transfected CHO cells. Furthermore, in the imiquimod-induced psoriasis-like mouse model, oral administration of S-26d for 1 week significantly alleviated modified psoriasis area and severity index scores (severity of erythema, scaliness, skin thickness) compared with the control group.

Pandemic Grief Reaction and Intolerance of Uncertainty on the Cognitive-Behavioral Model of COVID-Related Hypochondriasis Among Firefighters.

OBJECTIVE: This study aimed to explore the feasibility of cognitive-behavioral model hypochondriasis regarding coronavirus disease-2019 (COVID-19) among firefighters. In addition, we examined the possible role of their grief reaction and intolerance of uncertainty in the model of COVID-related hypochondriasis. METHODS: An anonymous online survey was done on October 27-28, 2022, among firefighters who witnessed people's death. Demographic characteristics were collected, and their psychological states were assessed using rating scales such as the Obsession with COVID-19 Scale (OCS), Coronavirus Reassurance-Seeking Behaviors Scale (CRBS), Fear of COVID-19 Scale (FCV-19S), Pandemic Grief Scale (PGS), and Intolerance of Uncertainty Scale-12 (IUS-12). RESULTS: Their OCS score was expected by the CRBS (ß=0.30, p<0.001), FCV-19S (ß=0.10, p<0.001), PGS (ß=0.29, p<0.001), and IUS12 (ß=0.04, p=0.024) (F=134.5, p<0.001). The COVID-related cognitive-behavioral model of hypochondriasis was feasible among firefighters who witnessed people's death. Their pandemic grief reaction and intolerance of uncertainty directly influenced their preoccupation with coronavirus, and viral anxiety and coronavirus reassurance-seeking behavior mediated the relationship. CONCLUSION: Firefighters' viral anxiety and coronavirus reassurance-seeking behavior mediated the influence of pandemic grief reaction or intolerance of uncertainty on the preoccupation with coronavirus.

The Effectiveness of a Neurofeedback-Assisted Mindfulness Training Program Using a Mobile App on Stress Reduction in Employees: Randomized Controlled Trial.

BACKGROUND: Mindfulness-based training programs have consistently shown efficacy in stress reduction. However, questions regarding the optimal duration and most effective delivery methods remain. OBJECTIVE: This research explores a 4-week neurofeedback-assisted mindfulness training for employees via a mobile app. The study's core query is whether incorporating neurofeedback can amplify the benefits on stress reduction and related metrics compared with conventional mindfulness training. METHODS: A total of 92 full-time employees were randomized into 3 groups: group 1 received mobile mindfulness training with neurofeedback assistance (n=29, mean age 39.72 years); group 2 received mobile mindfulness training without neurofeedback (n=32, mean age 37.66 years); and group 3 were given self-learning paper materials on stress management during their first visit (n=31, mean age 38.65 years). The primary outcomes were perceived stress and resilience scales. The secondary outcomes were mindfulness awareness, emotional labor, occupational stress, insomnia, and depression. Heart rate variability and electroencephalography were measured for physiological outcomes. These measurements were collected at 3 different times, namely, at baseline, immediately after training, and at a 4-week follow-up. The generalized estimating equation model was used for data analysis. RESULTS: The 4-week program showed significant stress reduction (Wald χ22=107.167, P<.001) and improvements in psychological indices including resilience, emotional labor, insomnia, and depression. A significant interaction was observed in resilience (time × group, Wald χ42=10.846, P=.02). The post hoc analysis showed a statistically significant difference between groups 1 (least squares mean [LSM] 21.62, SE 0.55) and 3 (LSM 19.90, SE 0.61) at the posttraining assessment (P=.008). Group 1 showed a significant improvement (P<.001) at the posttraining assessment, with continued improvements through the 1-month follow-up assessment period (LSM 21.55, SE 0.61). Physiological indices were analyzed only for data of 67 participants (22 in group 1, 22 in group 2, and 23 in group 3) due to the data quality. The relaxation index (ratio of alpha to high beta power) from the right electroencephalography channel showed a significant interaction (time × group, Wald χ22=6.947, P=.03), with group 1 revealing the highest improvement (LSM 0.43, SE 0.15) compared with groups 2 (LSM -0.11, SE 0.10) and 3 (LSM 0.12, SE 0.10) at the 1-month follow-up assessment. CONCLUSIONS: The study demonstrated that the neurofeedback-assisted group achieved superior outcomes in resilience and relaxation during the 4-week mobile mindfulness program. Further research with larger samples and long-term follow-up is warranted. TRIAL REGISTRATION: ClinicalTrials.gov NCT03787407; https://clinicaltrials.gov/ct2/show/NCT03787407.